WiMIR Workshop 2022 Project Guides

This is a list of Project Guides and their areas of interest for the 2022 WiMIR Virtual Workshop, which will take place as an online-only satellite event of ISMIR2022

The Workshop will take place on Monday 28 and Tuesday 29 November – please sign up by using this form.

We know that timezones for this are complicated, so we’ve made a Google Calendar with all the events on it – visit this link to add them to your calendar.

This year’s workshop is organized by Courtney Reed (Queen Mary University), Iris Yuping Ren (Utrecht University), Kitty Zhengshan Shi (Stanford University), and Jordan B.L. Smith (TikTok).

November 28

Vinod Vidwans: AI-Raga: A Mélange of the Musical and the Computational

This event will take place at 1600, GMT+5.5

AI-Raga is an artificially intelligent system that generates a musical composition in a given Raga without any human intervention. A close scrutiny of the treatises on Indian music shows that a computational perspective is inherently embedded in the ancient theories of music in India. It is an intellectual delight to decode the computational concepts from the vocabulary of Indian music, it also gives a sense of fructification and fulfilment to see these concepts successfully encoded in the system AI-Raga. In the vocabulary of Indian music certain concepts and principles viz. swara (a musical note), shruti (a microtone), Shadja-Panchama Bhava (the rule of fifths), and Shadja-Madhyama Bhava (the rule of fourths) have been rigorously theorized and well-established. This paper and presentation attempt to unravel the computational facets of these fundamental concepts and principles. It proves that a computational orientation of Indian music provides strong foundations for artificial creations and lends legitimacy to the aesthetic experience evoked. Based on the computational interpretation of these principles from the treatises viz. Natyashastra and Sangeet Ratnakara, the author has developed the aforementioned creative AI system that is yielding promising results. The latter part of the presentation involves a demonstration of the AI-Raga system. It is hoped that the audience will get many new insights into the role of Artificial Intelligence (AI) in the future of Indian music through this presentation.

Bio: Dr. Vinod Vidwans is a professor, in the Department of Design, Art and Performances at the FLAME University, Pune, India. Before joining FLAME University, he was a Senior Designer/ Professor at National Institute of Design (NID), Ahmedabad, India. He also headed the Departments of New Media and Software User Interface Design at NID. He has been a visiting faculty & a resource person at many prestigious institutes in India. He inherits Indic knowledge tradition and currently engaged in research on various Indic themes. He has designed and developed Artificial Intelligence (AI) Systems for Indian Music called `AI-Raga’ and `AI-Tala’. The AIRaga system generates a Bandish (a musical composition) on its own without any human assistance in a given Raga and renders it in traditional classical Indian style. The AI system generates a Bandish based on the Vadi, Samvadi, Aroha and Avroha of the Raga. It does not have any database of Ragas. The AITala system generates a Tabla performance in the given Tala.

Marcelo Queiroz: What do we look for in a research project?

This event will take place at 0900, GMT-3

The idea of this collaborative workshop is to brainstorm on the things that motivate participants to propose or join research projects, including goals (both personal and collective), frames of reference (theories, perspectives, aspirations), tools (models, algorithms, datasets), research practices (teamworking, interdisciplinarity, ethics), attitudes (the good, the bad and the ugly), among others that may be proposed on the spot. I’ll make a small introduction and share a personal perspective to get the ball rolling, and then open the floor for a horizontal debate.

Bio: Marcelo Queiroz is Associate Professor of the Computer Science Department and vice-coordinator of the Sonology Research Center at the University of São Paulo. His background includes a BSc in Computer Science, a BA in Music Composition, an MSc in Applied Mathematics, and PhD and Habilitation degrees in Computer Science. He was a visiting scholar at the Universities of Coimbra (Portugal), Maynooth (Ireland) and Thessaloniki (Greece). His research interests include sound/music/speech processing, computational acoustics, network and mobile music, and more generally computational techniques for music analysis/composition/performance/improvisation.

Kate Helsen: En-chanted: how medieval notation and Gregorian chant gets digital

This event will take place at 1000, GMT-5

Taking a ‘Digital Humanities’ approach to medieval chant means getting to tackle various interesting questions. First, there is the musical notation itself, which is unlike modern notation and requires specialized document analysis to be developed for the digital images of these manuscripts. Second, there is the enormous repertoire, mostly uncatalogued, which must be encoded in standard, efficient ways that will allow for large-scale comparative analysis and the discovery of local musical traditions or even just small, characteristic ‘riffs’. Third, we are looking at the implications of digital chant projects on our ability to know what it sounded like. In addition, chant melodies offer computer scientists the opportunity to work with various machine learning algorithms to think about these melodies as ‘strings’, analogous to language or even genetic strands of information. The results are as new as they are exciting – cross-disciplinary inspiration is mixed with musically rewarding results. 

Bio: Kate Helsen is an Assistant Professor in the Department of Music Research and Composition at the Don Wright Faculty of Music at the University of Western Ontario. Her specialization in plainchant, and Early Music more broadly, has led to her involvement in several international projects that dismantle the traditional boundaries of music and technology and have resulted in publications in Plainsong and Medieval MusicActa MusicologicaEmpirical Musicology Review and Early Music. Her research interests include early notations, the structural analysis of chant, melodic encodings, and obsessing over gorgeous manuscripts. Kate has sung professionally with the Tafelmusik Chamber Choir in Toronto since 2000. 

Sakinat Oluwabukonla Folorunso: ORIN: A Nigerian music benchmark dataset for MIR tasks and research.

This event will take place at 1730, GMT+1

Music is often seen as the only truly universal language. Nigerian music is typically used for relaxation, health therapy, ceremonials, war, work, etc. Music Information Retrieval (MIR) is the field of extracting high-level information, such as genre, artist recognition, or instrumentation from music. My talk will be based on presenting a new music dataset, namely the ORIN: A Nigerian music benchmark dataset for MIR tasks and research. ORIN is the first Nigerian music dataset and it consists of three categories of music: The traditional, English-Contemporary, and NaijArtist. The motivation is that to date, only a few research works have been done on Nigerian songs, the first publicly available robust benchmark dataset of Nigerian music to be openly shared in a Findable, Accessible, Interoperable and Reusable (FAIR) way and used to accelerate MIR tasks, AI models, and machine learning analysis, and train on Nigerian cultural values, for the African students and students in the diaspora. Firstly, I will talk about the ORIN dataset and the initial results that I got. I will also talk about feature importance and the use of SHAP (an XAI tool) in my work. I will then discuss the challenges faced and some open issues.

Bio: Sakinat Folorunso is a computer science lecturer in the Department of Mathematical Sciences, Computer Science unit at Olabisi Onabanjo University (OOU), Nigeria. She is the team lead for the Artificial Intelligence Research Group (ArIRSG) in OOU and the lead organizer for IndabaX, Nigeria. Her research focuses on music information retrieval, computer vision, machine learning, and Responsible Artificial Intelligence. More information about his research can be found on her home page.

November 29

Keunwoo Choi: How to get rejected from ISMIR and ICASSP for quite a few times and still feel OK.

This event will take place at 1530, GMT+9

This is yet another talk about failures; this time, in academia. I will talk about what I wanted, what I thought, what I thought wrong, and etc. during my preparation for and attending a PhD program. My submissions were rejected four times in a row within two years from ISMIR and ICASSP. It was frustrating but there were some lessons I could (try to) squeeze from — from that moments / retrospectively. Let’s talk about them, maybe there are something in common between us.

Bio: AI Research Director of Gaudio Lab. Research scientist at TikTok and Spotify, previously. PhD from Queen Mary University of London, Master and Bachelor from Seoul National University. Topics: music classification and recommendation, transcription, source separation, spatial audio, and audio synthesis.

Shantala Hegde: Neurocognitive deficits and how to repair it? Role of Music in Neuropsychological rehabilitation

This event will take place at 1400, GMT+5.5

Deficits in neurocognitive functions such as attention, memory, executive functions, language emotional and social functions form the sequelae of neurological, neurosurgical and neuropsychiatric conditions. These deficits are debilitating and determine functional recovery. Neuropsychological rehabilitation is an evidence-based treatment and the main goal is to enable patients to achieve their optimum level of functioning and overall well-being. Interventions to remediate cognitive deficits have often employed drill-based exercises- paper–pencil or computer-based tasks that focus on direct training of cognitive functions. Over the decade and half, there have been major advances in neuropsychological rehabilitation and newer methods are being used to provide the holistic method of intervention. Music based interventions are one such newer addition with a paradigm shift from social science approach to a neuroscience model. Music shares neural networks with other neurocognitive as well as motor functions. Music based interventions have been used to improve gait, neurocognitive, including socio-cognitive, speech as well as emotional domains of functioning. The need for further well-controlled trials is imperative and future research is the field of music and neuroscience has a crucial role to play in contributing to our better understanding of brain-behaviour and clinical recovery.

Bio: Dr. Shantala Hegde, is an Additional Professor and Consultant at the Neuropsychology Unit, Department of Clinical Psychology and Consultant to the Department of Neurorehabilitation, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru. She is the Intermediate Fellow of the prestigious Wellcome Trust UK-DBT India Alliance and is a mentee to Dr. Gottfried Schlaug, Professor of Neurology and Biomedical Engineering University of Massachusetts Chan Medical School – Baystate Medical Center Biomedical Engineering – IALS / UMass Amherst. Her other mentor as part of this fellowship is Dr. Matcheri S Keshavan, Stanley Cobb Professor and Academic Head of Psychiatry, Beth Israel Deaconess Medical Center and Massachusetts Mental Health Center, Harvard Medical School She is the first clinical psychologist to receive this prestigious fellowship in the country. She is the faculty-in-charge of the Music Cognition Lab at NIMHANS.

Fabien Gouyon and friends: A Day in the Life of a Music Track

This event will take place at 1700, GMT+0

The plan for this session is to interact with the audience on many different research areas that are relevant to music streaming (and digital audio entertainment generally). We’ll organize the session as the imaginary trip of a music track from its release in our catalog at SiriusXM/Pandora, to its recommendation to listeners. In parallel, this should provide you a tour of the type of scientific problems we face in an industrial context, and how we tackle them collaboratively.

Bio: Fabien GouyonChun GuoSergio OramasMatt McCallumElaine Mao, and Matthew Davies are some of the ML scientists at SiriusXM / Pandora, working from the United States and Europe on Music Information Retrieval, Recommender Systems, and Natural Language Processing. Applications of our research range from music content understanding, personalized algorithmic radio programming, to search & voice interaction, and more. Fabien is a former ISMIR President, now heading SiriusXM/Pandora Europe Science team. After an internship, Chun worked at Pandora since 2017 on many aspects of our products, ranging from search, voice, to algorithmic radio programming. Sergio also interned and then joined to build voice interaction features, he now works on music understanding and multimodal embeddings. Matt worked at Gracenote and Serato before joining in 2019, he currently works on machine listening. Elaine joined from Rdio in 2016 and works on Pandora homepage personalization. Matthew joined SiriusXM / Pandora after 15 years in academia.

Audrey Laplante: The discoverability of local content on global music streaming platforms

This event will take place at 1330, GMT-5

Algorithms are not neutral. Research has shown that they could be biased and produce results that are unfair or discriminatory in terms of gender, race or ethnicity, among other characteristics. On music streaming platforms, algorithms are used to classify music, determine how search results are ranked, create personalized playlists, and recommend playlists, songs or artists to a user. Could these algorithms be biased? In this workshop, we will look at the impact of algorithms on the discoverability of local content on global music streaming platforms. We will present an overview of what we know so far on this topic. We will then discuss how we could measure the discoverability of this content considering the opacity of algorithms and the lack of accessibility of user data. We will also discuss how we could study and compare what challenges these biases pose for artists, music labels, and/or end-users from different cultures.

Bio: Audrey Laplante is an associate professor at the Université de Montréal’s School of Library and Information Science. She is a member of the Centre for Interdisciplinary Research in Music Media and Technology (CIRMMT). She received a PhD (2008) and a Master’s (2001) in information science from McGill University and Université de Montréal, respectively, and an undergraduate degree in piano performance at Université de Montréal (1999). Her research interests include user studies, information practices, music information retrieval and discovery systems, and social media.


WiMIR Workshop 2022

We’re very pleased to say that we’ll be doing the fifth annual WiMIR Workshop this year. It will take place virtually across two dates, Monday 28 and Tuesday 29 November as a satellite event of ISMIR 2022.

The WiMIR Workshop will be two days of talks by eminent researchers in the WiMIR community, as well as time for networking, socializing, and discussion. The Workshop is, as ever, free and open to ALL members of the MIR community.  

We hope you can join us. We will have more information about the Workshop for you soon, and registration for it will be free and will open in late October.


WiMIR mentoring 2022 signups are now open!

Signups are now open for the seventh round of the Women in Music Information Retrieval (WiMIR) mentoring program, to run in 2022! We kindly invite previous and new mentors and mentees to sign up for the upcoming round.

The WiMIR mentoring program connects women students, postdocs, early-stage researchers, industry employees, and faculty to more senior women and men in MIR who are dedicated to increasing opportunities for women in the field. Mentors will share their experiences and offer guidance to support mentees in achieving and exceeding their goals and aspirations. The program also offers all mentors the option to pair up with a peer mentor for discussing relevant topics with a professional at a similar stage of their career. By connecting individuals of different backgrounds and expertise, this program strengthens networks within the MIR community, both in academia and industry.

Mentee eligibility

  • ​​You identify as women, trans, or non-binary, at any career stage in MIR.
  • This year we are also starting to expand the mentorship program to other underrepresented groups, pending an availability of mentors. If you are from a group that is underrepresented either at large in the ISMIR community (e.g., the Global South) or in the MIR community in your own country (e.g., an ethnic or racial group), we encourage community members of all genders to fill out this form if you are interested in receiving mentorship.
  • Sign up to GET a mentor: https://tinyurl.com/wimir-mentee-signup  

Mentor eligibility

Sign up by December 17, 2021. Mentoring to begin in February 2022.

Questions? Email: wimir-mentoring@ismir.net  

WiMIR Mentoring Program Team 2022

  • Johanna Devaney, Brooklyn College/Graduate Center (CUNY), United States
  • Lamtharn “Hanoi” Hantrakul, TikTok/ByteDance, Thailand
  • Michael Mandel, Reality Labs and Brooklyn College/Graduate Center (CUNY), United States
  • Francesca Ronchini, Inria, France

WiMIR Workshop 2021: A Virtual Success!

We’re pleased to say, again, that our virtual, distributed-in-time-and-space WiMIR Workshop 2021 went very well!

We had just under 200 signups this year, and did a two-day intensive across timezones from Tokyo to San Francisco. We were delighted to have speakers from Shanghai, Singapore, Denmark, Paris, and more!

We did longer talks this year, and then were on Discord as our socializing and networking space – we also resumed our discussions from Delft, covering Work/Life Balance, Burnout, Applying to Post Docs & Grad School, Picking An Advisor, Starting an MIR Business, and Interviewing.

Thanks to everyone who joined us! Special thanks to our volunteers:  Rachel Bittner, Jan Van Balen, Elio Quinton, Becky Liang, Meinard Mueller, Elena Georgieva – and extra-special thanks to our project guides: Dorien Herremans, Kat Agres, Tian Cheng, Stefania Serafin, Oriol Nieto, Emma Frid, Nick Bryan, Lamtharn “Hanoi” Hantrakul, Jason Hockman, Jake Drysdale, Olumide Okubadejo, and Cory McKay.

We’ll see you next year!

The WiMIR Workshop Organizers,

  • Courtney Reed, Queen Mary, UK
  • Kitty Shi, Stanford, USA
  • Jordan Smith, TikTok, UK
  • Thor Kell, Spotify, USA
  • Blair Kaneshiro, Stanford, USA

WiMIR Workshop 2021 Project Guides

This is a list of Project Guides and their areas of interest for the 2021 WiMIR Virtual Workshop, which will take place as an online-only satellite event of ISMIR2021.

The Workshop will take place on Friday, October 29 and Saturday, October 30 – please sign up by using this form: https://forms.gle/GHjqwaHWBciX9tuT7

We know that timezones for this are complicated, so we’ve made a Google Calendar with all the events on it – visit this link to add them to your calendar

This year’s Workshop is organized by Courtney Reed (Queen Mary University), Kitty Shi (Stanford University), Jordan B. L. Smith (ByteDance), Thor Kell (Spotify), and Blair Kaneshiro (Stanford University).

October 29

Dorien Herremans: Music Generation – from musical dice games to controllable AI models

This event will take place at 1500, GMT+8

In this fireside chat, Dorien will give a brief overview of the history of music generation systems, with a focus on the current challenges in the field, followed by an open discussion and Ask-Me-Anything (AMA) session. Prof. Herremans’ recent work has focused on creating controllable music generation systems using deep learning technologies. One challenge in particular – generating music with steerable emotion – has been central in her research. When it comes to affect and emotion, computer models still do not compare to humans. Using affective computing techniques and deep learning, Dorien’s team has built models that learn to predict perceived emotion from music. These models are then used to generate new fragments in a controllable manner, so that users can steer the desired arousal/valence level or tension in newly generated music. Other challenges tackled by Dorien’s team include ensuring repeated themes in music, automatic music transcription, and novel music representations, including the library Pytorch GPU library: nnAudio. 

Dorien Herremans is an Assistant Professor at Singapore University of Technology and Design, where she is also Director of Game Lab. Before joining SUTD, she was a Marie Sklodowska-Curie Postdoctoral Fellow at the Centre for Digital Music at Queen Mary University of London, where she worked on the project: “MorpheuS: Hybrid Machine Learning – Optimization techniques To Generate Structured Music Through Morphing And Fusion”. She received her Ph.D. in Applied Economics on the topic of Computer Generation and Classification of Music through Operations Research Methods, and graduated as a Business Engineer in Management Information Systems at the University of Antwerp in 2005. After that, she worked as a consultant and was an IT lecturer at the Les Roches University in Bluche, Switzerland. Dr. Herremans’ research interests include AI for novel applications in music and audio.

Kat Agres: Music, Brains, and Computers, Oh My!

This event will take place at 1600, GMT+8

In an informal, ask-me-anything chat, Kat will discuss her career path through cognitive science to computational approaches to music cognition, to her current research in music, computing and health.

Kat Agres is an Assistant Professor at the Yong Siew Toh Conservatory of Music (YSTCM) at the National University of Singapore (NUS), and teaches classes at YSTCM, Yale-NUS, and the NUS YLL School of Medicine. She was previously a Research Scientist III and founder of the Music Cognition group at the Institute of High Performance Computing, A*STAR. Kat received her PhD in Psychology (with a graduate minor in Cognitive Science) from Cornell University in 2013, and holds a bachelor’s degree in Cognitive Psychology and Cello Performance from Carnegie Mellon University. Her postdoctoral research was conducted at Queen Mary University of London, in the areas of Music Cognition and Computational Creativity. She has received numerous grants to support her research, including Fellowships from the National Institute of Health (NIH) and the National Institute of Mental Health (NIMH) in the US, postdoctoral funding from the European Commission’s Future and Emerging Technologies (FET) program, and grants from various funding agencies in Singapore. Kat’s research explores a wide range of topics, including music technology for healthcare and well-being, music perception and cognition, computational modeling of learning and memory, statistical learning, automatic music generation and computational creativity. She has presented her work in over fifteen countries across four continents, and remains an active cellist in Singapore.

Tian Cheng: Beat Tracking with Sequence Models

This event will take place at 1830, GMT+9

Beat tracking is an important MIR task with a long history. It provides basic metrical
information and is the fundament of synchronize-based applications. In this task, I
will summarize common choices for building a beat tracking model based on
research on related topics (beat, downbeat, and tempo). I will also compare simple
sequence models for beat tracking. In the last part, I will give some examples to show
how beat tracking is used in real-work applications.

Tian Cheng is a researcher at Media Interaction Group in National Institute of
Advanced Industrial Science and Technology (AIST), Japan. From 2016 to 2018, she
was a postdoctoral researcher in the same group. Her research interests include beat
tracking and music structure analysis. Her work provides basic music content
estimations to support applications for music editing and creation. She received her
PhD from Queen Mary University of London in 2016 and her dissertation focused on
using music acoustics for piano transcription.

Stefania Serafin: Sonic Interactions for All

This event will take place at 1800, GMT+2

In this workshop I will introduce our  recent work on using novel technologies and sonic interaction design to help hearing impaired users and individuals with limited mobility enjoy music.The talk will present the technologies we develop in the Multisensory Experience lab at Aalborg University in Copenhagen, such as VR, AR and novel interfaces and haptic devices, as well as how these technologies can be used to help populations in need.

Stefania Serafin is professor of Sonic Interaction Design at Aalborg University in Copenhagen. She received a Ph.D. in Computer Based Music Theory and Acoustics from Stanford University. She is the president of the Sound and Music Computing Association and principal investigator of the Nordic Sound and Music Computing Network. Her research interest is on sonic interaction design, sound for VR and AR and multi sensory processing.

Oriol Nieto: Overview, Challenges, and Applications of Audio-based Music Structure Analysis

This event will take place at 1000, GMT-7

The task of audio-based music structure analysis aims at identifying the different parts of a given music signal and labeling them accordingly (e.g., verse, chorus). The automatic approach to this problem can help several applications such as intra- and inter-track navigation, section-aware automatic DJ-ing, section-based music recommendation, etc. This is a fundamental MIR task that has significantly advanced over the past two decades, yet still poses several interesting research challenges. In this talk I will give an overview of the task, discuss its open challenges, and explore the potential applications, some of which have been employed at Adobe Research to help our users have better creative experiences.

Oriol Nieto (he/him or they/them) is a Senior Audio Research Engineer at Adobe Research in San Francisco. He is a former Staff Scientist in the Radio and Music Informatics team at Pandora, and holds a PhD from the Music and Audio Research Laboratory of New York University. His research focuses on topics such as music information retrieval, large scale recommendation systems, music generation, and machine learning on audio with especial emphasis on deep architectures. His PhD thesis is about trying to better teach computers at “understanding” the structure of music. Oriol develops open source Python packages, plays guitar, violin, cajón, and sings (and screams) in their spare time.

Emma Frid: Music Technology for Health

This event will take place at 2000, GMT+2

There is a growing interest in sound and music technologies designed to promote health, well-being, and inclusion, with many multidisciplinary research teams aiming to bridge the fields of accessibility, music therapy, universal design, and music technology. This talk will explore some of these topics through examples from two projects within my postdoctoral work at IRCAM/KTH: Accessible Digital Musical Instruments – Multimodal Feedback and Artificial Intelligence for Improved Musical Frontiers for People with Disabilities, focused on the design and customization of Digital Musical Instruments (DMIs) to promote access to music-making; and COSMOS (Computational Shaping and Modeling of Musical Structures), focused on the use of data science, optimization, and citizen science to study musical structures as they are created in music performances and in unusual sources such as heart signals. 

Emma Frid is a postdoctoral researcher at the Sciences et technologies de la musique et du sons (STMS) Laboratory, at the Institut de Recherche et Coordination Acoustique/Musique (IRCAM) in Paris, where she is working in the COSMOS project, under a Swedish Research Council International Postdoctoral Grant hosted by the Sound and Music Computing Group at KTH Royal Institute of Technology. She holds a PhD in Sound and Music Computing from the Division of Media Technology and Interaction Design at KTH, and a Master of Science in Engineering in Media Technology from the same university. Her PhD thesis focused on how Sonic Interaction Design can be used to promote inclusion and diversity in music-making. Emma’s research is centered on multimodal sound and music interfaces designed to promote health and inclusion, predominantly through work on Accessible Digital Musical Instruments (ADMIs).

Nick Bryan: Learning to Control Signal Processing Algorithms with Deep Learning

This event will take place at 1230, GMT-7

Expertly designed signal processing algorithms have been ubiquitous for decades and helped create the foundation of countless industries and areas of research (e.g. music information retrieval, audio fx, voice processing). In the last decade, however, expertly designed signal processing algorithms have been rapidly replaced with data-driven neural networks, posing the question — is signal processing still useful? And if so, how? In this talk, I will attempt to address these questions and provide an overview of we can combine both disciplines and use neural networks to control (or optimize) existing signal processing algorithms from data and perform a variety of tasks such as guitar distortion modeling, automatic removal of breaths and pops from voice recordings, automatic music mastering, acoustic echo cancelation, and automatic voice production. I will then discuss open research questions and future research directions with a focus on music applications.

Nicholas J. Bryan is a senior research scientist at Adobe Research and interested in (neural) audio and music signal processing, analysis, and synthesis. Nick received his PhD and MA from CCRMA, Stanford University and MS in Electrical Engineering, also from Stanford as well as his Bachelor of Music and BS in Electrical Engineering with summa cum laude honors at the University of Miami-FL. Before Adobe, Nick was a senior audio algorithm engineer at Apple and worked on voice processing algorithms for 4.5 years.

October 30

Lamtharn “Hanoi” Hantrakul: Transcultural Machine Learning in Music and Technology

This event will take place at 1600, GMT+8

Transcultural Technologies empower cultural pluralism at every phase of engineering and design. We often think of technology as a neutral tool, but technology is always created and optimized within the cultural scope of its inventors. This cultural mismatch is most apparent when tools are used across a range of contrasting traditions. Music and Art from different cultures, and the people that create and breathe these mediums, are an uncompromising sandbox to both interrogate these limitations and develop breakthroughs that empower a plurality of cultures. In this talk, we will be taking a deep dive into tangible audio technologies incubated in musical traditions from Southeast Asia, South Asia, South America and beyond.

Hanoi is a Bangkok-born Shanghai-based Cultural Technologist, Research Scientist and Composer. As an AI researcher, Hanoi focuses on audio ML that is inclusive of musical traditions from around the world. At Google AI, he co-authored the breakthrough Differentiable Digital Signal Processing (DDSP) library with the Magenta team and led its deployment across two Google projects: Tone Transfer and Sounds of India.  At TikTok, he continues to develop AI tools that empower music making across borders and skill levels. As a Cultural Technologist, Hanoi has won international acclaim for his transcultural fiddle “Fidular” (Core77, A’), which has been displayed in museums and exhibitions in the US, EU and Asia. He is fluent in French, Thai, English and is working on his Mandarin.

Jason Hockman + Jake Drysdale: Give the Drummer Some

This event will take place at 1000, GMT+1

In the late 1980s, popular electronic music (EM) emerged at the critical intersection between affordable computer technology and the consumer market, and has since grown to become the one of the most popular genres in the world. Ubiquitous within EM creation, digital sampling has facilitated the incorporation of professional-quality recorded performances into productions; one of the most frequently sampled types of recordings used in EM are short percussion solos from funk and jazz performances—or breakbeats. While these samples add an essential energetic edge to productions, they are generally used without consent or recognition. Thus, there is an urgency for the ethical redistribution of cultural value to account for the influence of a previous generation of artists. This workshop will present an overview on the topic of breakbeats and their relation to modern music genres as well as current approaches for breakbeat analysis, synthesis and transformative effects developed in the SoMA Group at Birmingham City University.

Jake Drysdale is currently a PhD student in the Sound and Music Analysis Group (SoMA) at Birmingham City University, where he specialises in neural audio synthesis and structural analysis in the electronic music genres. Jake leverages his perspective as an professional electronic music producer and DJ towards the development of intelligent music production tools that break down boundaries imposed by current technology.

Jason Hockman is an associate professor of audio engineering at Birmingham City University. He is a member of the Digital Media Technology Laboratory (DMTLab), in which he leads the Sound and Music (SoMA) Group for computational analysis of sound and music and digital audio processing. Jason conducts research in music informatics, machine listening and computational musicology, with a focus on rhythm and metre detection, music transcription, and content-based audio effects. As an electronic musician, he has had several critically-acclaimed releases on established international record labels, including his own Detuned Transmissions imprint.

Olumide Okubadejo: Ask Me Anything

This event will take place at 1800, GMT+2

Bring your industry questions for Spotify’s Olumide Okubadejo in this informal discussion, covering moving research into production, industry scale vs. academic scale, and moving between the two worlds.

Olumide Okubadejo was born and raised in Nigeria. The musical nature of the family he was born in and the streets he was raised in instilled in him early, a penchant for music. This appreciation for music led to him to play the drum in his local community by the age of 9. He later went on to learn to play the piano and the guitar by the age of 15. He studied for his undergraduate degree at FUTMinna, Nigeria, earning a Bachelor of Engineering degree in Electrical and Computer Engineering. He proceeded to University of Southampton, where he earned a masters degree in Artificial intelligence and then France where he earned a PhD. Since then he has focused his research around Machine learning for sound and music. These days, with Spotify, he researches and focuses on assisted music creation using machine learning.

Cory McKay: What can MIR teach us about music? What can music teach us in MIR?

This event will take place at 1300, GMT-4

Part of MIR’s richness is that it brings together experts in diverse fields, from both academia and industry, and gets us to think about music together. However, there is perhaps an increasingly tendency to segment MIR into discrete, narrowly defined problems, and to attempt to address them largely by grinding huge, noisy datasets, often with the goal of eventually accomplishing something with commercial applications. While all of this is certainly valuable, and much good has come from it, there has been an accompanying movement away from introspective thought about music, from investigating fundamental questions about what music is intrinsically, and how and why people create, consume and are changed by it. The goals of this workshop are to discuss how we can use the diverse expertise of the MIR community to do better in addressing foundational music research, and how we can reinforce and expand collaborations with other research communities.

Cory McKay is a professor of music and humanities at Marianopolis College and a member of the Centre for Interdisciplinary Research in Music Media and Technology in Montréal, Canada. His multidisciplinary background in information science, jazz, physics and sound recording has helped him publish research in a diverse range of music-related fields, including multimodal work involving symbolic music representations, audio, text and mined cultural data. He received his Ph.D., M.A. and B.Sc. from McGill University, completed a second bachelor’s degree at the University of Guelph, and did a postdoc at the University of Waikato. He is the primary designer of the jMIR software framework for performing multimodal music information retrieval research, which includes the jSymbolic framework for extracting musical features from digital scores, and also serves as music director of the Marianopolis Laptop Computer Orchestra (MLOrk).


WiMIR Workshop 2021

We’re very pleased to say that we’ll be doing the fourth annual WiMIR Workshop around ISMIR 2021 this year, on Friday, October 29 and Saturday, October 30.

Like last year, the event will be 100% virtual, mostly on Zoom! We’ll again offer programming across time zones and regions to make it easier for community members around the world to attend.  The Workshop is, as ever, free and open to ALL members of the MIR community.  

We hope you can join us – we’ll add more information about signups and our invited presenters soon!


Looking Back on WiMIR@ISMIR2020

As the ISMIR community organizes and prepares submissions for the ISMIR 2021 conference (to take place virtually November 8-12), let’s take a moment to reflect on the WiMIR events from last year’s conference! ISMIR 2020 was held October 11-15, 2020 as the first virtual ISMIR conference, with unprecedented challenges and opportunities. Slack and Zoom were used as the main platforms, which enabled the conference to designate channels for each presentation, poster and social space. With the support of WiMIR sponsors, substantial grants were given for underrepresented researchers, including women.

The ISMIR 2020 WiMIR events were organized by Dr. Claire Arthur (Georgia Institute of Technology) and Dr. Katherine Kinnaird (Smith College). A variety of WiMIR events took place during the conference, through which the ISMIR community showed support, shared ideas, and learned through thought-provoking sessions.

WiMIR Keynote

Dr. Johanna Devaney from the Brooklyn College and the Graduate Center, CUNY, gave an insightful keynote on our current comprehension and analysis of musical performance, The keynote, titled Performance Matters: Beyond the current conception of musical performance in MIR, was presented on October 13th.

WiMIR keynote video    

WiMIR keynote slides

Abstract: This talk will reflect on what we can observe about musical performance in the audio signal and where MIR techniques have succeeded and failed in enhancing our understanding of musical performance. Since its foundation, ISMIR has showcased a range of approaches for studying musical performance. Some of these have been explicit approaches for studying expressive performance while others implicitly analyze performance with other aspects of the musical audio. Building on my own work developing tools for analyzing musical performance, I will consider not only the assumptions that underlie the questions we ask about performance but what we learn and what we miss in our current approaches to summarizing performance-related information from audio signals. I will also reflect on a number of related questions, including what do we gain by summarizing over large corpora versus close reading of a select number of recordings. What do we lose? What can we learn from generative techniques, such as those applied in style transfer? And finally, how can we integrate these disparate approaches in order to better understand the role of performance in our conception of musical style?

Johanna Devaney is an Assistant Professor at Brooklyn College and the CUNY Graduate Center. At Brooklyn College she teaches primarily in the Music Technology and Sonic Arts areas and at the Graduate Center she is appointed to the Music and the Data Analysis and Visualization programs. Previously, she was an Assistant Professor of Music Theory and Cognition at Ohio State University and a postdoctoral scholar at the Center for New Music and Audio Technologies (CNMAT) at the University of California at Berkeley. Johanna completed her PhD in music technology at the Schulich School of Music of McGill University. She also holds an MPhil degree in music theory from Columbia University and an MA in composition from York University in Toronto.

Johanna’s research focuses on interdisciplinary approaches to the study of musical performance. Primarily, she examines the ways in which recorded performances can be used to study performance practice and develops computational tools to facilitate this. Her work draws on the disciplines of music, computer science, and psychology, and has been funded by the Social Sciences and Humanities Research Council of Canada (SSHRC), the Google Faculty Research Awards program and the National Endowment for the Humanities (NEH) Digital Humanities program.  

Twitter: Johanna Devaney (@jcdevaney)

“Notable Women in MIR” Meetups

This year’s WiMIR programming also included a series of meet-up sessions, each of which was an informal Q&A-type drop-in event akin to an “office hour”. In these sessions, participants had the opportunity to talk with the following notable women in the field.

Dr. Amélie Anglade is a freelance Music Information Retrieval and Machine Learning / Artificial Intelligence Consultant based in Berlin, Germany. She carried out a PhD on knowledge representation of musical harmony and modelling of genre, composer and musical style using machine learning techniques and logic programming at Queen Mary University of London (2014). After being employed as the first MIR Engineer at SoundCloud (2011-2013) and working for a couple of other music tech startups, she is now offering (since 2014) freelance MIR and ML/AI services to startups, larger companies and institutions in Berlin and remotely. Her projects range from building search and recommendation engines to supporting product development with Data Science solutions, including designing, implementing, training and optimising MIR features and products. To her clients she provides advice, experimentation, prototyping, production code implementation, management and teaching services. During her career she has worked for Sony CSL, Philips Research, Mercedes-Benz, the EU Commission, Senzari, and Data Science Retreat, among others.

Dr. Rachel Bittner is a Senior Research Scientist at Spotify in Paris. She received her Ph.D. in Music Technology in 2018 from the Music and Audio Research Lab at New York University under Dr. Juan P. Bello, with a research focus on deep learning and machine learning  applied  to fundamental frequency estimation. She has a Master’s degree in mathematics from New York University’s Courant Institute, as well as two Bachelor’s degrees in Music Performance and in Mathematics from the University of California, Irvine.

In 2014-15, she was a research fellow at Telecom ParisTech in France after being awarded the Chateaubriand Research Fellowship. From 2011-13, she was a member of the Human Factors division of NASA Ames Research Center, working with Dr. Durand Begault. Her research interests are at the intersection of audio signal processing and machine learning, applied to musical audio. She is an active contributor to the open-source community, including being the primary developer of the pysox and mirdata Python libraries.

Dr. Estefanía Cano is a senior scientist at AudioSourceRe in Ireland, where she researches topics related to music source separation. Her research interests also include music information retrieval (MIR), computational musicology, and music education. She is the CSO and co-founder of Songquito, a company that builds MIR technologies for music education. She previously worked at the Agency for Science, Technology and Research A*STAR in Singapore, and at the Fraunhofer Institute for Digital Media Technology IDMT in Germany.

Dr. Elaine Chew is a senior CNRS (Centre National de la Recherche Scientifique) researcher in the STMS (Sciences et Technologies de la Musique et du Son) Lab at IRCAM (Institut de Recherche et Coordination Acoustique/Musique) in Paris, and a Visiting Professor of Engineering in the Faculty of Natural & Mathematical Sciences at King’s College London. She is principal investigator of the European Research Council Advanced Grant project COSMOS and Proof of Concept project HEART.FM. Her work has been recognised by PECASE (Presidential Early Career Award in Science and Engineering) and NSF CAREER (Faculty Early Career Development Program) awards, and Fellowships at Harvard’s Radcliffe Institute for Advanced Study. She is an alum (Fellow) of the NAS Kavli and NAE Frontiers of Science/Engineering Symposia. Her research focuses on the mathematical and computational modelling of musical structures in music and electrocardiographic sequences. Applications include modelling of music performance, AI music generation, music-heart-brain interactions, and computational arrhythmia research. As a pianist, she integrates her research into concert-conversations that showcase scientific visualisations and lab-grown compositions.

Dr. Rebecca Fiebrink is a Reader at the Creative Computing Institute at University of the Arts London, where she designs new ways for humans to interact with computers in creative practice. Fiebrink is the developer of the Wekinator, open-source software for real-time interactive machine learning whose current version has been downloaded over 40,000 times. She is the creator of the world’s first MOOC about machine learning for creative practice, titled “Machine Learning for Artists and Musicians,” which launched in 2016 on the Kadenze platform. Much of her work is driven by a belief in the importance of inclusion, participation, and accessibility: she works frequently with human-centred and participatory design processes, and she is currently working on projects related to creating new accessible technologies with people with disabilities, designing inclusive machine learning curricula and tools, and applying participatory design methodologies in the digital humanities. Dr. Fiebrink was previously an Assistant Professor at Princeton University and a lecturer at Goldsmiths University of London. She has worked with companies including Microsoft Research, Sun Microsystems Research Labs, Imagine Research, and Smule. She holds a PhD in Computer Science from Princeton University.

Dr. Emilia Gómez is Lead Scientist of the HUMAINT team that studies the impact of Artificial Intelligence on human behaviour at the Joint Research Centre, European Commission. She is also a Guest Professor at the Department of Information and Communication Technologies, Universitat Pompeu Fabra in Barcelona, where she leads the MIR (Music Information Research) lab of the Music Technology Group and coordinates the TROMPA (Towards Richer Online Music Public-domain Archives) EU project.

Telecommunication Engineer (Universidad de Sevilla, Spain), Msc in Acoustics, Signal Processing and Computing applied to Music (ATIAM-IRCAM, Paris) and PhD in Computer Science at Universitat Pompeu Fabra, her work deals with the design of data-driven algorithms for music content description (e.g. melody, tonality, genre, emotion) by combining methodologies from signal processing, machine learning, music theory and cognition. She has been contributing to the ISMIR community as author, reviewer, PC member, board and WiMIR member and she was the first woman president of ISMIR. 

Dr. Blair Kaneshiro is a Research and Development Associate with the Educational Neuroscience Initiative in the Graduate School of Education at Stanford University, as well as an Adjunct Professor at Stanford’s Center for Computer Research in Music and Acoustics (CCRMA). She earned a BA in Music; MA in Music, Science, and Technology; MS in Electrical Engineering; and PhD in Computer-Based Music Theory and Acoustics, all from Stanford. Her MIR research focuses on human aspects of musical engagement, approached primarily through neuroscience and user research. Dr. Kaneshiro is a member of the ISMIR Board and has organized multiple community initiatives with WiMIR, including as co-founder of the WiMIR Mentoring Program and WiMIR Workshop. 

Dr. Gissel Velarde, PhD in computer science and engineering, is an award-winning researcher, consultant and lecturer specialized in Artificial Intelligence. Her new book: Artificial Era: Predictions for ultrahumans, robots and other intelligent entities, presents a groundbreaking view of technology trends and their impact on our society. 

Additionally, she published several scientific articles in international journals and conferences, and her research has been featured in the media by Jyllands-Posten, La Razón, LadoBe and Eju. She earned her doctoral degree from Aalborg University in Denmark in 2017, an institution recognized as the best university in Europe and fourth in the world in engineering according to the US News World Ranking and the MIT 2018 ranking. She obtained her master’s degree in electronic systems and engineering management from the University of Applied Sciences of South Westphalia, Soest in Germany, thanks to a DAAD scholarship, and she holds a licenciatura’s degree in systems engineering from the Universidad Católica Boliviana, recognized as the third best university in Bolivia according to the Webometrics Ranking 2020. 

Velarde has more than 20 years of experience in engineering and computer science. She was a research member in the European Commission’s project: Learning to Create, was a lecturer at Aalborg University, and currently teaches at the Universidad Privada Boliviana. She worked for Miebach Gmbh, Hansa Ltda, SONY Computer Science Laboratories, Moodagent, and Pricewaterhouse Coopers, among others. She has developed machine learning and deep learning algorithms for classification, structural analysis, pattern discovery, and recommendation systems. In 2019 & 2020 she was internationally selected as one of 120 technologists by the Top Women Tech summit in Brussels.

Dr. Anja Volk (MA, MSc, PhD), Associate Professor in Information and Computing Sciences (Utrecht University) has a dual background in mathematics and musicology which she applies to cross-disciplinary approaches to music. She has an international reputation in the areas of music information retrieval (MIR), computational musicology, and mathematical music theory. Her work has helped bridge the gap between scientific and humanistic approaches while working in interdisciplinary research teams in Germany, the USA and the Netherlands.  Her research aims at enhancing our understanding of music as a fundamental human trait while applying these insights for developing music technologies that offer new ways of interacting with music. Anja has given numerous invited talks worldwide and held editorships in leading journals, including the Journal of New Music Research and Musicae Scientiae. She has co-founded several international initiatives, most notably the International Society for Mathematics and Computation in Music (SMCM), the flagship journal of the International Society for Music Information Retrieval (TISMIR), and the Women in MIR (WIMIR) mentoring program. Anja’s commitment to diversity and inclusion was recognized with the Westerdijk Award in 2018 from Utrecht University, and the Diversity and Inclusion Award from Utrecht University in 2020. She is also committed to connecting different research communities and providing interdisciplinary education for the next generation through the organization of international workshops, such as the Lorentz Center in Leiden workshops on music similarity (2015), computational ethnomusicology (2017) and music, computing, and health (2019).

WiMIR Grants

Thanks to the generous contributions of WiMIR sponsors, a number of women received financial support to cover conference registration, paper publication, and – for the first time in 2020 – childcare expenses. In all, WiMIR covered registration costs for 42 attendees; covered publication fees for 3 papers; and provided financial support to cover child-care expenses for 4 attendees.

Thank you WiMIR Sponsors!





WiMIR Mentoring Call for Organizers 2021

Dear ISMIR community,

Women in Music Information Retrieval (WiMIR) is seeking new organizers for the WiMIR Mentoring Program.

Now in its 6th round, the WiMIR mentoring program connects women, trans, and non-binary students, postdocs, early-stage researchers, industry employees, and faculty to more senior women and allies in MIR who are dedicated to increasing opportunities for underrepresented community members. By connecting individuals of different backgrounds and expertise, this program strengthens networks within the MIR community, in both academia and industry. 

We are seeking motivated peers from the MIR community who can commit to serving as organizer for at least 2 years.

The responsibilities of this role are as follows (responsibilities are distributed among the organizers and average around 2 hours per month per organizer):

  • Prepare and distribute signup forms; match applicants into mentor-mentee pairs (Fall/Winter).
  • Announce the pairs and serve as a support resource during the mentoring round (Winter/Spring).
  • Create and distribute evaluation forms; review evaluations and integrate into the next mentoring round (Summer).
  • Prepare and/or present summary slides on the mentoring program for the ISMIR conference and other community presentations as needed (Fall/year round).
  • Supervise and delegate program tasks to a team of 2-3 student volunteers; recruit new volunteers as needed (year round).
  • Author blog posts announcing the start and end of each mentoring round (Winter/Summer).
  • Maintain and update organizational materials, and onboard new organizers (year round).

Sign up here: https://forms.gle/44z6kSNj8D1kgxzE9 

Signups will close March 31, 2021, and we will notify and begin onboarding new organizers around May 15, 2021.

Questions? Email wimir-mentoring@ismir.net.


Johanna Devaney, Michael Mandel, and Eva Zangerle

WiMIR Mentoring Program Organizing Committee


Inspiring Women in Science: An Interview with Dr. Dorien Herremans

Believing in the importance of shedding light on the stories of successful women in the Music Information Retrieval (MIR) field, we are happy to share our interview with Dr. Dorien Herremans, the second Inspiring Women in Science interview. Dr. Herremans is an Assistant Professor at Singapore University of Technology and Design and Director of Game Lab. She has a joint-appointment at the Institute of High Performance Computing, A*STAR and works as a certified instructor for the NVIDIA Deep Learning Institute. Her research interests include machine learning and music for automatic music generation, data mining for music classification (hit prediction) and novel applications at the intersection of machine learning/optimization and music.

Whereabouts did you study? 

I completed a five-year masters degree in business engineering (in management information systems) at the University of Antwerp. I spent the next few years living in the Swiss Alps, where I was an IT lecturer at Les Roches, Bluche, and had my own company as a web developer. I returned to the University of Antwerp to obtain my PhD in Applied Economics. My dissertation focused on the use of methods from operations research and data mining in music, more specifically for music generation and hit prediction. I then got a Marie-Sklodowsi postdoctoral fellowship and joined the Centre for Digital Music (C4DM), at Queen Mary University of London to develop Morpheus, a music composition system with long-term structure based on tonal tension. After my postdoc I joined Singapore University of Technology and Design, where I am an assistant professor and teach data science and AI. My lab focuses on using AI for audio, music and affective computing (AMAAI), I’m also Director of the SUTD Game Lab and have a joint appointment at the Institute for High Performance Computing, A*STAR.  

What are you currently working on?

Some of our current projects include a Music Generation system based on emotion (aiMuVi); music transcription; a GPU-based library for spectrogram extraction (nnAudio); multi-modal predictive models (from video/audio/text) on emotion and sarcasm detection. 

When did you first know you wanted to pursue a career in science?

It happened rather naturally. When I was about to graduate, I felt more of a pull towards staying in academia versus going into industry. Especially because at the time, with a degree in business engineering, that would have most probably meant joining the big corporate world. As a 24 year old, I instead wanted to keep exploring new things, stay in the dynamic environment of academia, especially since I could do so while living in a very quaint mountain village. 

How did you first become interested in MIR?

During my last year as a student in business engineering, I was looking for a master thesis topic and came across ‘music and metaheuristics’. Having been passionate about music my whole life, I jumped at the opportunity to combine mathematics with music. This started an exciting journey in the field of MIR, a field I did not know existed at that time (2004). 

What advice would you give to women who are interested in joining the field of MIR but don’t know where to begin?

We are fortunate to have a growing community of MIR researchers. Through groups such as WiMIR or ISMIR, you can join mentoring programs and get in touch with researchers who have more experience in the field. If you are a beginning researcher, you could also attend one of the conferences and start building a network. 

How is life in Singapore? Is there a difference for your research between working in Europe and Asia?

My first impression when arriving in Singapore a few years ago, was that it felt very much like living in the future. It’s quite an amazing country, efficient, safe, warm (hot really), and with amazingly futuristic architecture. As a researcher, Singapore offers great funding opportunities and a dynamic environment. We have been growing the AMAAI lab steadily, and are excited to connect with other music researchers in Singapore (there are more than you might think!). 

You are working on AI and music now which is a fascinating field. What can it do and cannot now?

After almost a decade of science fiction movies that play around with the concept of AI, people seem to equate AI with machines obtaining self-awareness. That’s not what we should think of as AI these days. I see (narrow) AI systems as models that learn from historical data, extract patterns, and use that to make predictions on new data. Narrow AI focuses on clearly defined problems, whereas general AI is more challenging and tries to cope with more generalised tasks. In MIR we typically develop narrow AI systems, and due to the recent developments in neural network technologies and the increasing GPU power, we are making large strides. The challenges that we are currently facing are in large part related to the lack of labeled data in music, and the cross-domain expertise required to leverage music knowledge in AI systems. 

How to make human musicians and AI musicians work together and not compete with each other?

This will be the natural first step. Unless properly educated about AI, many people will not trust AI systems to take on tasks on their own. I believe this is why many of the personal assistant AI systems are given female names and voices (exudes trust?). For example, a composer might not want a system to generate music automatically,  but they might appreciate a computer-aided-composition system, which, for instance, gives them an initial suggestion for how to harmonise their composed melody. 

It seems still some distance for it to be useful in daily life compared with face/voice recognition. What is your expectation for that field?

I actually think that AI in music is being integrated in our daily lives, through companies such as Spotify, Amazon Music, etc. as well as through smaller startups such as AIVA. I expect the number of startups in the music tech area to increase strongly in the coming years. 

You are also working on combining emotion and music together. On what level do you think the computer can understand human emotion?

The word ‘understand’ is tricky here. We can train models to predict our perceived or experienced emotion based on observations we have done in the past, however, the biggest challenge seems to be: why are different people experiencing different emotions when listening to the same piece of music? 

These days more and more people work in different fields with AI. For the students working on music and AI, can you give them some guidance about their research strategy and career path?

As for any research topic, I would recommend students to tackle a problem that they are fascinated by. Then you dive deep into the topic and explore how it can be advanced even further. To stick with a topic, it’s essential that you are passionate about it. 

Can you give a few tips for people working at home in the days of Covid-19? 

Stay inside, get as much exercise as you can, and try to think of this as the perfect time to do undisturbed research…

To keep up to date with Dr. Herremans, you can refer to https://dorienherremans.com/

Rui Guo graduated with a Master’s Degree in Computer Science from the Shenzhen University, China. Currently he is a third year PhD student in University of Sussex, UK pursing his PhD degree in music. His research topic is AI music generation with better control and emotional music generation.


Our lives during the COVID-19 pandemic

2020 was definitely a strange year. It felt shorter than ever. With vaccines becoming available in more countries, I am hoping that there is a better future for us. Also, that we can meet in real person for next year’s ISMIR.

Since we were not able to see each other for the last year ISMIR, I wanted to share our community members’ 2020 story by conducting a survey with questions related to work, hobbies and general lifestyle. A total of 62 people have responded (thank you!) and I would like to share some results.


Majority of people did like working from home! 

But online meetings, not so much…We like talking to real people. 

More than 50% of people said they were less productive last year. Don’t feel bad if you feel like you didn’t achieve much! If you managed to stay healthy last year, that is the biggest achievement.

I asked the members to share one good thing about working from home. In terms of work impacts, people reported less distraction; a more flexible schedule and efficient work – “I can do things with my own rhythm”, “No need to go to the office (which means saving time, and also less environmental impact)“; and more equality between remote and “local” employees. Respondents also reported positive outcomes for family life (e.g., “Being able to see my daughter throughout the day”). Finally, working from home was perceived as positive in its integration with home life – for instance in terms of food (e.g., “No need to eat on the road.” “Eating better food”) and a comfortable work environment (e.g., “Comfortable couch”, “Could listen to music without headphones”) – as well as lifestyle: “Fitting exercise, cooking, and music practice into my day”, “Can play with my dog”, “Not having to wear pants ;)”, “Wearing pajamas all day :D”.


It seems like many of us were able to put more time into our hobbies. Same goes for me! 

Also, quite a lot of people found new hobbies. 

Our members shared some of their hobbies. As music lovers, there were many hobbies related to music: making music, playing instruments, jamming online, singing, DJing, hosting radio shows and learning music. In fact,  71% of us listened to more music compared to last year! I assume there is a correlation with COVID-19 situation. Plus, there were lots of physical activities, such as running, cycling and yoga. Some of us enjoyed baking, cooking and even brewing kombucha! Meditating, knitting, drawing, reading and gardening also were mentioned several times. 


Staying healthy mentally and physically seem to be the greatest challenge these days. I personally had to consciously remind myself to move and stay calm. It definitely wasn’t easy. I think I managed to find some balance finally in December.

With increased time at home, I personally learned a lot about myself. It gave me time to reflect on my life once again and I was able to remind myself what is important in my life. 

So I asked, “Is there anything new that you discovered about yourself during the pandemic?” and found 4 common responses.

First, there were people who discovered that they enjoy remote working and staying home – “I don’t get bored!”, “I’m more OK than I thought with extended alone-time”, “I should stay at home more often than I used to”.  Some even mentioned they were able to build good routines.  Opposite to the first, the second most common response was the realization of how interactions with people are important in their lives – “how much I depend on physical connections with friends”, “That I am more of a people person than I ever suspected”. Some said they would rather go to the office than stay home (Me too!). Third common response was that they felt the need to physically move more and spend time outdoors – “I’m unfit for living as a hermit”,  “don’t underestimate the power of breaks in the sunshine”. It seems like many of us learned that physical activities not only improve physical, but also mental health. Last common response was the need for discipline. Having 100% control over our time and this freedom appeared to be attractive, but in fact, it requires a lot of effort to keep everything on track.

Here are some additional memorable responses: “I am living in a more privileged condition than I have realized”, “I can cook!”, “That we need to enjoy life” and  “That I’ve actually been living pretty much like this even before.” 


Everyone misses pre-covid days. Our community members told us that they miss live concerts and festivals, hanging out with real people and travelling the most. 

Let’s not give up hope, so that we can meet again soon. Please don’t forget to take care of the environment to prevent this kind of pandemic in the future. 

As a closing note, we asked people to share one tip they have for the community to survive this time. 

The most mentioned tip was to stay healthy physically and mentally. Some suggestions include getting a good sleep, eating good food, moderately exercising and doing mediation. Staying connected with others and helping others were a runner-up tip. Although we already have enough zoom talks, non-work related zoom socializing can actually make us feel better, like zoom beers! 

Also many emphasized having a routine or some rule, such as setting a certain time slot for work and break. Don’t think too much about how others have been doing; breathe and focus on yourself 🙂 

There were some extra fun and useful tips: “Don’t let the dirty dishes accumulate”, “fix things in your house”, “learn new things”,  and “TableTop simulator (on Steam) was quite useful during lockdown”. 

Stay healthy and happy till we meet next time !!


Kyungyun Lee is a MSc student at Music and Audio Computing Lab, KAIST. Her research interests range from MIR to HCI. Currently, she is interested in automatic music generation and analyzing user interaction with music platforms.


WiMIR Workshop 2020: Success!

We’re pleased to tell you that our highly virtual, distributed-in-time-and-space WiMIR Workshop for 2020 went pretty well, all things considered!

Rather than put everything on a single day, we wanted to spread the event out – both to avoid Zoom fatigue, and to allow folks across different timezones to join in easily. We ended up running four sessions across eight weeks, ranging from Pacific Daylight Time to Indian Standard time. We had speakers from India, Australia, California, Europe, and had over 450 signups!

We had each of our presenters give a 45 minute talk about their work and career, and then followed it up with a socializing & networking session. We took advantage of Zoom’s breakout rooms to send folks into rooms of 4-6 people for twenty minutes or so. We did this twice, and then the remaining people met in the main Zoom call for a very relaxed end-of-call discussion.

Thanks to everyone who joined us, for every session! Special thanks to our volunteers:  Jay Appaji, Phoebe Chua, Elena Georgieva, Rui Guo, Kyungyun Lee, Alia Morsi, & Elona Shatri – and extra-special thanks to our project guides:  Christine Bauer, Tom Collins, Daniel Ellis, Jenn Thom, Doug Turnbull, Amanda Krause, Preeti Rao, Rohit M. A., Juanjo Bosch, Amy LaMeyer, & Darragh Dandurand.  

We’ll see you next year!

The WiMIR Workshop Organizers,


WiMIR Workshop 2020 Project Guides

This is a list of Project Guides and their areas of interest for the 2020 WiMIR Virtual Workshop, which will take place as an online-only satellite event of ISMIR2020.

These events are FREE and open to the public, but advance sign-up is REQUIRED. Sign up here: https://bit.ly/WiMIRWorkshop2020

This year’s Workshop is organized by Blair Kaneshiro (Stanford University), Katherine M. Kinnaird (Smith College), Jordan B. L. Smith (ByteDance), and Thor Kell (Spotify).

Please note that start times vary for each event – see each event for exact time and time zones, or view a GMT calendar of all events here.

August 22

Daniel Ellis: Sound Event Recognition

This event will start at 10:00 AM, Eastern Daylight Time – copy to your calendar, in your time zone.

My group at Google has been working on developing general-purpose sound event recognizers.  I’ll briefly recap the evolution of this work from its origins from virtually nothing in 2014 to deployed apps today.  I’ll also talk a little about my own transition from academia to industry, and the day-to-day details of my work as a Tech Lead – Research Scientist – Manager at Google.

Dan Ellis leads a small team developing sound event recognition technologies within Google AI/Perception.  From 2000-2015 he was on the faculty of the Electrical Engineering department at Columbia University, leading research into environmental sound processing and music audio analysis. He now regrets encouraging his students to write Matlab without unit tests.

Jenn Thom: Improving the Music Listening Experience: HCI Research at Spotify

This event will start at 1:00 PM, Eastern Daylight Time – copy to your calendar, in your time zone.

Music plays an important role in everyday life around the world. People rely on music to manage their mood, express their identity and celebrate milestone events. Streaming services like Spotify have transformed the way that people consume audio by providing listeners with multiple personalized ways to access an abundant catalog of content. In my talk, I will describe several active areas of HCI research at Spotify and present our work on understanding how people search for music and how we can enable exploration for listeners. 

Jenn Thom leads the HCI research lab at Spotify. Her current research interests include understanding how people search for and describe music and developing novel design and prototyping methods for conversational interactions. Prior to joining Spotify, she was a Research Scientist at Amazon where she worked on collecting and mining data to bootstrap new features for the launch of the Echo. She was also a Research Staff Member at IBM Research where she studied how employees used social networks for intercultural collaboration. Jenn received her PhD from Cornell University and her dissertation focused on how people expressed territorial behaviors in user-generated content communities.

September 5

Hadas Kress-Gazit Nelly Andasawis-Puri Photo/Robyn Wishna 2018

Doug Turnbull: Locally-Focused Music Recommendation

This event will start at 12:00 PM, Eastern Daylight Time – copy to your calendar, in your time zone.

There are talented musicians all around us. They play amazing live shows at small venues in every city all around the world. Yet music services like Spotify, Apple Music, YouTube, and Pandora do a poor job of helping listeners discover these artists for a variety of commercial and technical reasons. To remedy this problem, I will discuss our recent efforts to use recommender systems to support locally-focused music discovery. First, I’ll provide a brief introduction to recommender systems, the long-tail consumption models, and popularity bias. I’ll then describe how we can adapt typical recommender system algorithms to be better at recommending local (long-tail) music. Finally, I will describe a personalized Internet radio project called MegsRadio.fm, why it failed after years of dedicated development, and how lessons learned are being incorporated into the design of my new project called Localify.org.

Doug Turnbull is an Associate Professor in the Department of Computer Science at Ithaca College. His research focuses on music information retrieval, computer audition, machine learning, and human computation. His research passion is using recommender systems to promote music by talented local artists. He is currently working on Localify.org which explores using music event recommendations and playlist generation on Spotify to support local music communities. This project is funded by the National Science Foundation and being developed by a large team of undergraduate students at Ithaca College. He is a former ISMIR conference program co-chair and former ISMIR board member. More information about his research can be found at https://dougturnbull.org.

Amanda Krause: Everyday Experiences of Music: A Fireside Chat with Dr. Amanda Krause 

This event will start at 6:00 PM, Pacific Daylight Time – copy to your calendar, in your time zone.

Given the prominence of music in our everyday lives and developmental shifts in technology, how do people access, consume, and respond to music? Working in the social and applied psychology of music, Dr. Amanda Krause researches how our everyday experiences with music influence our well-being, in order to better understand the place that music occupies in modern life. In this fireside chat, Amanda will discuss her research topics and approaches, how she has pursued her research interests via travel, education, and collaboration, and the challenges and opportunities that have arisen from establishing an inter-disciplinary research career. She will also reflect on how the MIR and music psychology disciplines intersect, how she has made connections within the MIR community, and how researchers working in these disciplines can collaborate to tackle some very interesting and challenging research questions. 

This fireside chat will be moderated by Dr. Blair Kaneshiro.

As a music psychology scholar based at James Cook University, Dr. Amanda Krause studies how we experience music in our everyday lives. Her research asks how our musical experiences influence our well-being. Amanda’s current projects examine the role of music listening and the radio in supporting individual and community well-being. Amanda is the author of numerous academic publications and currently serves on the Australian Music & Psychology Society (AMPS) committee. She has also spoken on her research to academics and industry leaders at conferences around the world, to students through programs like Skype A Scientist and STEM Professionals in Schools, and to members of the general public via radio appearances and events like Pint Of Science.

September 19

Preeti Rao and Rohit M. A.: Unity in Diversity: MIR Tools for Non-Western Music

This event will start at 1:30 PM, India Standard Time – copy to your calendar, in your time zone.

Just as there is so much linguistic and cultural diversity, there is rich diversity in music across the globe. But the universals of musical structure and attributes such as pitch, rhythm and timbre that describe all music enable us to apply the rich tools of MIR developed for Western music to interesting and musically relevant tasks in genres as distinct as Indian art music. We discuss some important considerations for researchers such as (i) identifying MIR-addressable problems and the tools to apply, and (ii) dealing with the anticipated limitations of labeled datasets. We do this with easy to follow examples from Indian music and show how the insights obtained can be rewarding, also in terms of understanding the music better!

Preeti Rao has been on the faculty of Electrical Engineering at I.I.T. Bombay, teaching and researching in the area of signal processing with applications in speech and audio. She received her Ph.D. from the University of Florida in Gainesville in 1990. She was a collaborator in the CompMusic project during 2011-2016 for the application of MIR to non-Western music, led by the MTG at UPF, Barcelona. She currently leads another international collaboration funded by the Government of India for research in Computational Musicology and Musical Instruments Modeling for Indian Music. She has been actively involved in development of technology for Indian music and spoken language learning applications. She co-founded SensiBol Audio Technologies, a start-up incubated by I.I.T. Bombay in 2011, with her Ph.D. and Masters students.

Rohit is a Master’s student and a research assistant in the Digital Audio Processing lab in the Electrical Eng department at IIT Bombay. His background is in communication and digital signal processing and his research interests lie in MIR, computational musicology and machine learning for audio. His current research is centered around developing tools for analysis of the Hindustani classical art form and instruments, with a focus on studying performance related aspects. He is also a trained violinist.

Juanjo Bosch: AI-Assisted Music Creation

This event will start at 2:00 PM, Central European Summer Time – copy to your calendar, in your time zone.

This workshop will give an overview of the usage of music information retrieval and more generally artificial intelligence for assisting composers and producers when making music, from both a research and an industry perspective. We will talk about some of the recent advancements in machine learning applied to (audio and symbolic) music generation and repurposing, and we will review some of the techniques that paved the way there. We will also look at how startups and large companies are approaching this field, some of the real-world applications that have been created, and we will finally discuss some specific examples of how artists and coders have been using such technologies. Could we even try to imagine what the future of this exciting field may look like?

Juanjo is a Research Scientist working at the Creator Technology Research Lab at Spotify, whose main mission is to create tools for musicians / producers. He holds a Telecommunications Engineering degree from Universitat Politécnica de Valencia, a Masters (in Sound and Music Computing) and PhD from the Universitat Pompeu Fabra (Music Technology Group, Barcelona), which was conducted under the supervision of Emilia Gómez. He has also visited other academic institutions such as the University of Sheffield, Queen Mary University of London (C4DM), and worked for three years at Fraunhofer IDMT. Before joining Spotify, he already had experience in the industry including Hewlett Packard and Yamaha Music. His main research interests lie at the intersection of music information retrieval and AI-assisted music creation.

Amy LaMeyer and Darragh Dandurand: XR and Music – A Conversation

This event will start at 9:00 AM, Pacific Daylight Time – copy to your calendar, in your time zone.

Extended reality (XR) is radically changing the way we create, consume, and socialize around music. In this conversation, Amy LaMeyer and Darragh Dandurand will discuss today’s landscape of XR and music, including the current state of the industry, recent technological advances, and innovations in artist-fan connections in the age of COVID. They’ll also speak about the history and mission of the WXR Fund, and reflect upon her own professional journey and what it means to forge an authentic career path.

Amy LaMeyer is Managing Partner at the WXR Fund investing in early stage companies with female leadership that are transforming business and human interaction using spatial computing (VR/AR) and AI.  She has been named one of the people to watch in AR by Next Reality. Amy is the author of ‘Sound and AR’ in the book “Convergence: how the world will be painted with data”.  She has 20 years of experience in a high growth technology industry in corporate development, mergers and acquisitions, engineering and finance.

Darragh Dandurand is an award-winning creative director, brand strategist, photojournalist, and curator who has worked in media for a decade and now in immersive technology / spatial computing, as well. Recent clients include a number of media outlets and studios, such as Refinery29, VICE, Verizon, the New Museum, Buck Co, Superbright, Sensorium, iHeartMedia and Wallplay.  Currently, Darragh is consulting creative tech teams, developing her own experiential projects, publishing articles on mixed-reality, and researching and presenting on the intersection of fashion, e-commerce and wearable tech. She sits on the board of directors for the Femme Futures Grant via The Kaleidoscope Fund. Darragh has lectured at Stanford University, Temple University, University of Maryland, University of Rhode Island, The New School, and the Fashion Institute of Technology, as well as VRARA Global Summit, Samsung, Out in Tech,  MAVRIC, Magic Leap’s LeapCon, and others.

October 3

Christine Bauer: The *Best Ever* Recommendation – For Who? And How Do You Know That?

This event will start at 11:00 AM, Central European Summer Time – copy to your calendar, in your time zone.

Music recommender systems are an inherent ingredient of all kind of music platforms. They are meant to assist users in searching, sorting, and filtering the huge repertoire. Now, if a recommender computes the *best ever* recommendation. Is it the best choice for the user? Or the best for the recommended artist? Is it the best choice for the platform provider? Is the *best ever* recommendation equally valuable for users, artists, and providers alike? If you (think you) have an answer, how do you know that? Is it indeed the *best ever* recommendation? In this session, I will provide insights on what we miss out on in research on music recommenders. I will point to the perspectives of the various stakeholders and to the sphere of methods that may allow us to shed light upon answers to questions that we have not even asked so far. I will *not* provide the ultimate answer. I do not know it. It is research in progress. The goal is to move forward together. Expect this session to be interactive with lots of brainstorming and discussion.

Christine Bauer is an assistant professor at Utrecht University, The Netherlands. Her research activities center on interactive intelligent systems. She focuses on context-adaptive systems and, currently, on music recommender systems in particular. Her activities are driven by her interdisciplinary background. She holds a Doctoral degree in Social and Economic Sciences, a Diploma degree in International Business Administration, and a Master degree in Business Informatics. Furthermore, she pursued studies in jazz saxophone. Christine is an experienced teacher and has been teaching a wide spectrum of topics in computing and information systems across 10 institutions. She has authored more than 90 papers, received the prestigious Elise Richter grant, and holds awards for her research as well as her reviewing activities. Earlier, she researched at Johannes Kepler University Linz, Austria, WU Vienna, Austria, University of Cologne, Germany, and the E-Commerce Competence Center, Austria. In 2013 and 2015, she was Visiting Fellow at Carnegie Mellon University, Pittsburgh, PA, USA. Before starting her academic career, she worked at Austria’s biggest collecting society AKM. More information can be found on her website: https://christinebauer.eu

Tom Collins: Automatic Music Generation: Demos and Applications

This event will start at 1:00 PM, British Summer Time – copy to your calendar, in your time zone.

There has been a marked increase in recent years in the number of papers and algorithms addressing automatic music generation (AMG). This workshop will:

  • Invite participants to try out some tweak-able demos and applications of music generation algorithms;
  • Cover some of my lab’s projects in this area, which include a recent collaboration with Grammy Award-winning artist Imogen Heap, and integrating AMG algorithms into computer games;
  • Review approaches and applications from other research groups, such as Google Magenta;
  • Underline that a literature existed on this topic before deep learning(!), and that evaluation should consist of more than optimizing a metric.

Tom studied Music at Cambridge, Math and Stats at Oxford, and did his PhD on automatic pattern discovery and music generation at the Open University. He has held multiple postdoc and visiting assistant professor positions in the US and Europe, and now splits his time between University of York (where he runs the Music Computing and Psychology Lab) and the music cooperative MAIA, Inc.


WiMIR Workshop 2020

WiMIR Logo

We are delighted to announce that the WiMIR 3rd Annual Workshop will take place as a series of weekend events before the start of the virtual ISMIR 2020.  We’re also delighted to again be an official satellite event of the ISMIR conference!

Due to the virtual-ness of ISMIR this year, we’re changing our format:  Each workshop date will feature talks by top researchers in the field, followed by small-group social sessions — all in Zoom.  This year, we are making a special effort to offer programming across time zones and regions, to make it easier for our colleagues who are not near Montreal to attend.  The Workshop is, as ever, free and open to ALL members of the MIR community.  

Our dates for the Workshop will be August 22, September 5, September 19, and October 3.  We hope you can join us – we’ll add more information about signups and our invited presenters soon!


Inspiring Women in Science: an interview with Dr. Blair Kaneshiro

Why are women still so underrepresented in science? Female scientists represent only a third of researchers globally, and things are not getting better when talking about information and communication technologies, where less than a fifth of the graduates are women.
The Music Information Retrieval (MIR) community is no exception, with less than 20% female participation at ISMIR 2019, the conference of the International Society for Music Information Retrieval. Despite the efforts of organizers this year to promote diversity in the choice of the keynote and the session chairs, the gender gap is still evident when looking at the author and attendee statistics.

Much still needs to be done to bring women into the community and to reduce the gender gap. For this purpose, Women in Music Information Retrieval (WiMIR) – a group of people within ISMIR – has put together ideas and started a number of diversity and inclusion initiatives. The goal is to build a community around women in the field and create a network able to support young researchers through grants, workshops and mentoring from senior scientists. Thanks to the WiMIR grants, ISMIR 2019 female participation had a 5% increase!

I am starting a series of interviews with female researchers in MIR to find out more about their experiences and give an insight to young female researchers who want to start a career in MIR research. The first name on my list is Dr. Blair Kaneshiro, who is a researcher at the Center for Computer Research in Music and Acoustics (CCRMA) at Stanford University, a member of the ISMIR Board, and one of the WiMIR organizers.

Whereabouts did you study? 

I’m from the United States and completed all of my schooling at Stanford University. My undergraduate degree was in Music. I later returned for graduate school, completing an MA in Music, Science, and Technology; MS in Electrical Engineering; and finally a PhD in Computer-Based Music Theory and Acoustics.

When did you first know you wanted to pursue a career in science?

A career interest in science for me did not develop until graduate school. I had been working at an education company at Stanford called the Education Program for Gifted Youth (EPGY) after my undergraduate degree when Patrick Suppes – co-founder of EPGY and Emeritus Professor of Philosophy, among many other remarkable things – suggested I pursue graduate work. Dr. Suppes was actively running a neuroscience lab at that time, and offered to fund my Master’s through a research assistantship in his lab. Once there, I began to see how neuroscience and engineering could be employed to address fundamental questions about perception and music – questions I feel, three graduate degrees and over a decade later, I’ve still barely begun to answer! Sadly, Dr. Suppes passed away in 2014. I am forever grateful for his support and mentorship, and for encouraging me to pursue science in the first place. I try to pay forward what I have learned from him, as both a scientist and a mentor.

How did you first become interested in MIR?

For the first few years of my graduate study, I didn’t feel I had a ‘home’ research community as my work was falling somewhere between perception / cognition and machine learning / brain decoding. In 2011, my classmate suggested I attend the ISMIR conference. I was immediately drawn in by the field of MIR, not only by the research topics – which to me were combining computation, perception, and application in exciting ways – but also by the community itself, which was welcoming and open to new ideas and approaches.

What are you currently working on?

These days I have two main research tracks. The first is electroencephalography (EEG) research, where I continue to use the decoding techniques I first encountered in the Suppes lab, and related approaches, to study proximity spaces of neural responses. I’m also working with analysis techniques that enable us to study neural processing of ‘natural’ stimuli (e.g., real-world music). My second area of research focuses on how social practices around music selection and consumption are supported (or not) by present-day technologies such as streaming platforms – more in the direction of user research. In all, I really enjoy working with a variety of collaborators, study designs, data modalities, and analysis techniques to gain a better understanding of how we humans engage with music.

Are there still gender imbalances in your research environment and in the MIR community? If yes, how can we overcome that?

Yes, definitely! In fact, I was relatively unfazed by the low number of women at the first ISMIR conference I attended, if only because it was what I was used to from being in engineering classes. But there is definitely an imbalance. In terms of overcoming this challenge, the MIR community stands out in its willingness to take action. Community members (women and men) have signed on to mentor women, organize initiatives, lead Workshop groups, and serve on conference committees; and sponsors contribute extra travel funds specifically for women to attend the ISMIR conference. While there is still a lot of progress to be made, the fact that the community as a whole is already on board makes a huge difference in moving forward.

Which changes, if any, are needed in the MIR community to be more attractive to women?

Building a more diverse research community will take time. It also requires support at multiple career stages, from recruiting women into the field to retaining those who are here. We are already starting to see positive outcomes from community initiatives. For instance, the WiMIR Mentoring Program, WiMIR Workshop, and WiMIR Travel Awards can serve as entry points for newcomers to the field, and we have seen cases of WiMIR Mentoring participants pivoting into MIR-related jobs or graduate programs, and of newcomers attending ISMIR for the first time through WiMIR Travel Awards and returning in future years as full-paper authors. But how exactly does one progress from attendee to author? And how do we keep women in the field for the long term – what are the challenges there? Will our progress in recent years translate to long-term change? I hope we can all continue to examine these challenges, understand underlying factors and biases, and take steps – on a community level and in our immediate working environments – to recruit and retain more women in MIR.

What advice would you give to young girls who are considering a career in science?

I recommend taking a broad look at what types of scientific fields are out there. Maybe you have a picture in your mind of what it looks like to ‘do science’. In fact, science spans a vast array of disciplines – even music! Also, it’s important to recognize that there is no one way to be a scientist, and no one way to look or act as a scientist. I highly recommend browsing the profiles at #UniqueScientists to see just how diverse the people, topics, and career paths in science are today.

Giorgia Cantisani graduated with a Master’s Degree in Biomedical Engineering from the Polytechnic University of Turin and, since September 2018, is a PhD student at Télécom Paris in France. Her research interests range from music information retrieval (MIR) to neuroscience. In particular, she is interested in the analysis of brain responses to music and how these can be used to guide and inform MIR tasks.


Introducing the WiMIR Editorial team, and Issuing a Call for Contributions!

Women in Music Information Retrieval (WiMIR) is very excited to introduce the WiMIR Editorial Team! In this blog post, we introduce the team members, our goals, and most importantly, how you can collaborate with us!

Meet the 2020-2022 Team

Alia Morsi, Masters student in Sound and Music Computing at Universitat Pompeu Fabra, Spain. My current research interests are MIR for enhancing music education.

Giorgia Cantisani, PhD student in Audio Signal Processing at Télécom Paris, France. My current research interest is MIR, brain responses to music and source separation.

Kyungyun Lee, Masters student in Music and Audio Computing Lab at KAIST, South Korea. My current research interest is music performance generation and HCI.

Rui Guo, PhD Student in Music at University of Sussex, England. My current research is to generate symbolic music compositions by AI.

Saul Ivan Rivas Vega, Masters student at IIMAS of the UNAM, México. I’m interested in MIR using AI models as tools for performers and to generate autonomous compositions.


The WiMIR Editorial team is supervised by Blair Kaneshiro, PhD (Stanford University).

What are the team objectives? In a nutshell, our work revolves around:

  • Maintaining the WiMIR blog
  • Coordinating and managing community contributions, and presenting them in a meaningful way.

We strongly emphasize the second point, because in addition to posts that announce WiMIR initiatives, we would like to expand the blog’s content to include other types of interesting material, and in that we strongly encourage community involvement

Call for Contributions

Suggestions include the following ideas:

  • Reflection on a topic related to WiMIR mentoring (e.g., networking, work-life balance, jobs in industry or academia, applying to graduate school, dealing with sexism).
  • Reflection on personal experiences as a woman, underrepresented minority, or ally in MIR.
  • Review of a book, article, paper, or other resource related to mentoring or otherwise supporting diversity and inclusion.
  • Review of a conference, workshop, meetup, concert, or other event that is relevant to the aims of WiMIR.
  • Review of research, codebase, creative work, or other contribution by a woman or other underrepresented minority in MIR or related field.
  • Tips for newcomers to MIR as a research field and/or community.

But also, feel free to suggest more topics! Blog posts are contributions from community members, so this is where everyone can help.

  • If you would like to write a blog post, please submit a form with some initial info about your idea: https://bit.ly/WiMIRBlogPost  
  • If you have any topic ideas, feedback, or comments, please contact us at wimir-editorial@googlegroups.com
  • Also, your support is important! So we hope you enjoy reading our posts and also sharing them with others who might be interested. In addition to the community driven blog posts, we will be publishing a set of interviews so stay tuned!

WiMIR Mentoring Round 2020

The fifth round of the WiMIR mentoring program is about to start!

Mentors and mentees have been matched and introduced to each other by the Mentoring Program Committee.  Participants come from 6 continents, Europe, North and South America, Asia, Oceania and Africa.

Thanks everyone for contributing and keeping your commitment! Happy mentoring!

WiMIR mentoring 2020 participants

Mentoring Program Committee

  • Johanna Devaney, Brooklyn College, USA
  • Ryan Groves, Melodrive, Germany
  • Blair Kaneshiro, Stanford University, USA
  • Anja Volk, Utrecht University, Netherlands
  • Eva Zangerle, University of Innsbruck, Austria
  • Michael Mandel, Brooklyn College, USA

Mentoring Student Volunteers

  • Yun-Ning Hung, Georgia Tech, USA
  • Arshiya Gupta, University of San Francisco, USA
  • Francesca Ronchini, Universitat Pompeu Fabra, Spain


We thank our generous mentors from Europe, North and South America, and Asia for dedicating their time to this program:

  • Ajay Srinivasamurthy, Amazon.com, Inc, USA
  • Alexander Lerch, Georgia Institute of Technology, USA
  • Amruta Vidwans, Pindrop, USA
  • Andrew Demetriou, Delft University of Technology, Netherlands
  • Andrew McLeod, EPFL, Switzerland
  • Andy Sarroff, iZotope, USA 
  • Anja Volk, Utrecht University, Netherlands
  • Anne McKinnon, The Boolean, USA
  • Ashis Pati, Georgia Tech, USA
  • Ashley Burgoyne, University of Amsterdam, Netherlands
  • Ayinde Alakoye, nēdl, USA
  • Bertrand Scherrer, LANDR Audio Inc., Canada
  • Blair Kaneshiro, Stanford University, USA
  • Brian McFee, New York University, USA
  • Chih-Wei Wu, Netflix, Inc., USA
  • Chris Donahue, Stanford, USA
  • Christine Bauer, Johannes Kepler University Linz, Austria
  • Christopher Tralie, Ursinus College, USA
  • Dan Ellis, Google, USA
  • Delia Fano Yela, Chordify, Netherlands
  • Doğaç Başaran, Audible Magic, USA
  • Douglas Eck, Google, USA
  • Douglas Turnbull, Ithaca College, USA 
  • Elio Quinton, Universal Music Group, USA
  • Emilia Gomez, Joint Research Centre and Universitat Pompeu Fabra, Spain
  • Emilia Parada-Cabaleiro, Complutense University of Madrid, Spain
  • Emmanouil Benetos, Queen Mary University of London, United Kingdom
  • Eric Nichols, Zillow Group, USA
  • Erling Wold, Audible Magic, USA 
  • Fabien Gouyon, Pandora, USA
  • Furkan Yesiler, Music Technology Group, UPF, Spain
  • Gabriel Meseguer Brocal, IRCAM, France
  • Gabriel Vigliensoni, McGill University/Goldsmiths, Canada
  • Gaël Richard, Telecom Paris, Institut Polytechnique de Paris, France
  • Geoffroy Peeters, Telecom Paris, France
  • Helena Cuesta, Universitat Pompeu Fabra, Spain
  • Ichiro Fujinaga, McGill University, Canada
  • Ioannis Petros Samiotis, Delft University of Technology (TU Delft), Netherlands
  • Jan Van Balen, University of Antwerp, Belgium
  • Jin Ha Lee, University of Washington, USA
  • Joe Cheri Ross, Linkedin, USA
  • Johan Pauwels, Queen Mary University of London, United Kingdom
  • Johanna Devaney, Brooklyn College, USA
  • Jon Gillick, UC Berkeley, USA
  • Jonathan Driedger, Chordify, Netherlands
  • Jordan Smith, Tik Tok, USA
  • Juhan Nam, KAIST/NYU, South Korea/USA
  • Justin Salamon, Adobe, USA
  • Magdalena Fuentes, NYU, USA
  • Makarand Velankar, MKSSS’S Cummins College of Engineering, India
  • Marcelo Caetano, McGill University, Canada
  • Marcelo Queiroz, University of São Paulo, Brazil
  • Marius Miron, European Commission, Spain
  • Mark Cartwright, New York University, USA
  • Matthew Davies, INESC TEC / University of Coimbra, Portugal
  • Matthew McCallum, Pandora Media, USA
  • Maximos Kaliakatsos-Papakostas, Athena Research and Innovation Centre, Greece
  • Meinard Mueller, International Audio Laboratories Erlangen, Germany
  • Mi Tian, Spotify, USA
  • Oriol Nieto, Pandora, USA
  • Prem Seetharaman, Northwestern University, USA
  • Rachel Bittner, Spotify, USA
  • Rafael Valle, NVIDIA and UC Berkeley, USA
  • Robin Laney, Open University, United Kingdom
  • Ryan Groves, Arcona, Germany
  • Sebastian Rosenzweig, International Audio Laboratories Erlangen, Germany
  • Sertan Şentürk, Kobalt Music Group, USA 
  • Siddharth Gururani, Georgia Institute of Technology, USA
  • So Yeon Park, Stanford, USA
  • Srikanth Cherla, Moodagent, Denmark
  • Stefan Sullivan, Smule, USA 
  • Tejaswinee Kelkar, University of Oslo, Norway
  • Théis Bazin, Sony CSL Paris, France
  • Tom Collins, University of York, USA
  • Vincent Lostanlen, Cornell Lab of Ornithology, USA
  • Zafar Rafii, Gracenote, USA
  • Zhiyao Duan, University of Rochester, USA 

Our mentors and mentees are coming from all around the world, as you can see from the map. 


They range from university faculty members to industry employees, and represent a diverse field of interests and backgrounds, such as signal processing, machine learning, computer science, information technology, ethnomusicology, computational musicology, music theory, music composition, music perception and cognition, music performance, music and mathematics, neuroscience, library science, music education, multimedia research, sound design and data analytics, among others while exploring new and interesting areas in music research.


WiMIR Workshop 2019: Success!

We’re very pleased, again, to write to tell you that the WiMIR 2nd Annual Workshop was a resounding success!

Like last year, we wanted the WiMIR Workshop to  build upon the MIR community’s already strong support for diversity and inclusion. We had three main aims:

  • Encourage the discussion of proposed or unfinished work.
  • Amplify the scientific efforts of women in the field.
  • Create additional space for networking.

Thanks to support from Spotify and Pandora, we were able to offer the WiMIR Workshop as a free event, open to everyone!  The Workshop took place as a satellite event of ISMIR2019, at the amazing Aula Conference Centre in Delft.  We had just over 100 people attend, with twelve Project Guides.  Our topics ranged from doing research-at-scale to ethical frameworks for music technology, analysis of computer-generated folk music, and more.  We also had amazing catering and eight kinds of flavoured water – thanks Delft!



The day was a bit more streamlined compared to last year – we focused more on group work with the Project Guides, and did not do a poster session.  We had a similar lunch session to last year, informally structured around topics like “Dealing with Sexism” and “Surviving Grad School”.  The lunch provided attendees with an opportunity to connect with new people and learn about topics that members in the field (especially those who are not women) don’t often discuss.

After lunch, the project groups started a deeper dive into their topic areas, with an eye to present at 4:30 pm and then conduct an hour-long science fair at 5:00.  You can see a Twitter thread of all the talks here, and look at the final presentation slides here!



It was a lot of fun, and we got lots of excellent feedback – we’re looking forward to next year.

And, of course, the tweets:

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Thanks so much to everyone who helped out: The Aula Conference Centre staff, the ISMIR2019 volunteers & General Chairs, the ISMIR Board, WIMIR leadership and TU Delft!

We’ll see you next year in Montréal!

The WiMIR Workshop Organizers,



WiMIR Workshop 2019 Project Guides


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This is a list of Project Guides and their areas of interest for the 2019 WiMIR Workshop, which will take place on Sunday, 3rd November 2019 as a satellite event of ISMIR2019.  These folks will be leading the prototyping and early research investigations at the workshop.

This year’s Workshop is organized by Blair Kaneshiro (Stanford University), Katherine M. Kinnaird (Smith College), Thor Kell (Spotify), and Jordan B. L. Smith (Queen Mary University of London) and is made possible by generous sponsorship from Pandora and Spotify.

Planning to attend the WiMIR Workshop?
Read about the Project Guides and their work in detail below, and sign up to attend at https://forms.gle/mCEod8AvtqnBcMJz7


Amelie Anglade

Ryan Groves

Amélie Anglade and Ryan Groves:  Auto-BeatSaber: Generating New Content for VR Music Games

In this workshop we will dive into a specific problem at the intersection of music, gaming, and dance: the generation of a BeatSaber song level. BeatSaber is one of the most popular VR titles, in which the core of the gameplay is to rhythmically slice incoming boxes with light sabers to the sound of the beat. The game has sparked a huge community of modders who create their own choreographies to existing songs, as well as MIR-based tools (such as a MIDI converter or a BPM estimator) designed specifically to support level creation. The task of this workshop will be: how could we use machine learning to generate these choreographies automatically? Participants will have the opportunity to learn from our experience as Data Science & MIR consultants as we will share our own structured process for problem-solving in the music tech industry.

Dr. Amélie Anglade is a Music Information Retrieval and Data Science consultant. She completed her PhD at Queen Mary University of London, before moving to industry, initially taking on positions in R&D labs such as Sony CSL, Philips Research and CNRS, and then being employed as an MIR expert for Music Tech startups such as SoundCloud and frestyl. For the past 5 years she has further developed her expertise in music identification and discovery–assisting startups and larger companies in the AI and music or multimedia space as an independent consultant, researching, prototyping, and scaling up Machine Learning solutions for them. Additionally, Amélie is a contributor to the EU Commision as an independent technical expert in charge of reviewing proposals and ongoing EU projects. In her spare time she attends music hackathons (15+ so far), and is a teacher and mentor for women in the field of data science through multiple organizations.

Ryan Groves is an award-winning music researcher and veteran developer of intelligent music systems. He received his Master’s in Music Technology from McGill University. In 2016, his work on computational music theory was awarded the Best Paper at ISMIR. He also has extensive experience in industry, building musical products that leverage machine learning. As the former Director of R&D for Zya, he developed a musical messenger app that automatically sings your texts, called Ditty. Ditty won the Best Music App of 2015 by the Appy Awards. More recently, he co-founded Melodrive, where he and his team built the first artificially intelligent composer that could compose music in realtime and react to interactive scenarios such as games and VR experiences. He now works as a consultant and startup advisor in Berlin, with a focus on expanding the use cases of music and audio through the application of AI.

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Ashley Burgoyne: Cognitive MIR with the Eurovision Song Contest

When Duncan Laurence triumphed at the 2019 Eurovision Song Contest in Tel Aviv, it was the Netherlands’ first victory in the contest since 1975 – and perfect timing for the ISMIR conference! One of the most-watched and discussed broadcasts in Europe, data about the Song Contest are an excellent opportunity to link the patterns we can find using MIR tools in audio to real-world human behaviour. This workshop will show you how, and teach you techniques you can use wherever you want to use MIR to understand not just music but also people.

We will consider a number of questions. Every year, the bookmakers try to predict the contest winner: can MIR do better? The same songwriters write the songs for multiple countries each year: is there nonetheless a typical sound for each country’s entry? People assume that voting is politically rather than musically based, but recent research has called those assumptions into question: what does the music tell us? And can we link Eurovision tracks to what fans say on Twitter or direct experimentation about what they hear?

John Ashley Burgoyne is the Lecturer in Computational Musicology at the University of Amsterdam and part of the Music Cognition Group at the Institute for Logic, Language, and Computation. Dr Burgoyne teaches in both musicology and artificial intelligence and is especially interested in musicometrics: developing behavioural and audio models that are conceptually sound, reliable, and musicologically interpretable as music enters the digital humanities era. He was the leader of the Hooked on Music project, an online citizen science experiment to explore long-term musical memory that attracted more than 170,000 participants across more than 200 countries.

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Estefanía Cano and Jakob Abeßer: Learning about Music with MIR

What does John Coltrane have in common with Cannonball Adderley? What makes micro-timing in Brazilian samba unique? What are the tuning characteristics of the harpsichord? Which cues do musicians use to control ensemble intonation? The MIR community has been working for decades in developing reliable methods for research tasks such as beat tracking, melody estimation, chord detection, music tagging, among many others. While most of these methods are not yet perfect, they can certainly be useful tools when attempting to answer questions as the ones above. This holds true especially if computational analysis tools are combined with the experience from musicians, the insights from human listeners, and music knowledge.

This workshop will focus on exploring ways in which we can gain new knowledge about music by combining available MIR techniques and human musical expertise. Instead of focusing on improving MIR methods or in proposing new ways to solve MIR tasks, we want to use this workshop as a platform to brainstorm new questions about the various aspects of music. We want to revisit old questions and propose new alternatives to address them. We want to look back at previous projects and studies, and use the lessons we learned to improve the way we address questions today.

Estefanía Cano is a research scientist at the Semantic Music Technologies group at Fraunhofer IDMT in Germany. Estefanía received her B.Sc. degree in electronic engineering from the Universidad Pontificia Bolivariana, Medellín- Colombia, in 2005, her B.A. degree in Music- Saxophone Performance from Universidad de Antioquia, Medellín-Colombia, in 2007, her M.Sc. degree in music engineering from the University of Miami, Florida, in 2009, and her Ph.D. degree in media technology from the Ilmenau University of Technology, Germany, in 2014. In 2009, she joined the Semantic Music Technologies group at the Fraunhofer Institute for Digital Media Technology IDMT as a research scientist. In 2018, she joined the Social and Cognitive Computing Department at the Agency for Science, Technology and Research A*STAR in Singapore. Her research interests include sound source separation, music education, and computational musicology.

Jakob Abeßer studied computer engineering (Dipl.-Ing., 2008) and media technology (Dr.-Ing., 2014) at the Ilmenau University of Technology. Since 2008, he has been working in the field of semantic music processing at the Fraunhofer Institute for Digital Media Technologies (IDMT) in Ilmenau. In 2005 and 2010 he spent 2 stays abroad at the Université Paul Verlain in Metz, France and the Finnish Centre of Excellence in Interdisciplinary Music Research at the University of Jyväskylä in Finland. Between 2012 and 2017, he also worked as a doctoral researcher in the Jazzomat Research Project at the Franz Liszt School of Music in Weimar, developing methods for the computer- aided analysis of jazz improvisations. Since 2018 he is working as co-investigator of the research project “Informed Sound Activity Detection in Music Recordings” (ISAD) at Fraunhofer IDMT in collaboration with Prof. Dr. Meinard Müller from the International Audio Laboratories in Erlangen, Germany. His current research interests include music information retrieval, machine listening, music education, machine learning and deep learning.

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Matthew Davies and Sebastian Böck:  Building and Evaluating a Musical Audio Beat Tracking System

The task of musical audio beat tracking can be considered one the foundational problems in the music information retrieval community. In this workshop we seek to take a tour of the entire beat tracking pipeline by addressing the following steps: i) how to manually annotate ground truth ii) how to construct a lightweight beat tracking model using deep neural networks; iii) how to select appropriate musical material for training and testing; and iv) how to conduct evaluation in a musically meaningful way. In each of these areas, we seek to provide practical hands-on experience and acquired tacit knowledge concerning what works and also what doesn’t work. Throughout the workshop we will promote active participation and discussion with the aim of driving new research in beat tracking and fostering new collaborations.

Matthew Davies is a music information retrieval researcher with a background in digital signal processing. His main research interests include the analysis of rhythm in musical audio signals, evaluation methodology, creative music applications, and reproducible research. Since 2014, Matthew has coordinated the Sound and Music Computing Group in the Centre for Telecommunications and Multimedia at INESC TEC. From 2014-2018, he was an Associate Editor for the IEEE/ACM Transactions on Audio, Speech and Language Processing and coordinated the 4th Annual IEEE Signal Processing Cup. He was a keynote speaker at the 16th Rhythm Production and Perception Workshop, and General Chair of the 13th International Symposium on Computer Music Multidisciplinary Research.

Sebastian Böck received his diploma degree in electrical engineering from the Technical University in Munich in 2010 and his PhD in computer science from the Johannes Kepler University Linz in 2016. Within the MIR community he is probably best known for his machine learning-based algorithms, which pushed the performance of automatic beat tracking and other tasks into regions formerly only achievable by humans. Currently he is continuing his research at the Austrian Research Institute for Artificial Intelligence (OFAI) and the Technical University of Vienna.

Georgi Dzhambazov

Georgi Dzhambazov: Verse and Chorus Detection of Acoustic Cover Versions

Many MIR tasks have as a prerequisite the annotation of structural segments of a song. While cover versions usually retain most music aspects of the original song, there could be a completely new structure (sections appended/missing). In particular, covers with acoustic instrumental accompaniment are characterized by a predominant vocal line, whereby the accompaniment is occasionally missing or improvised. Therefore structure detection algorithms based solely on harmonic features are most likely not a sufficient solution.

In this hands-on-workshop, we will explore the problem of automatic segmentation and labeling of the verse and chorus sections for a given vocal cover version with acoustic accompaniment. Information about the original song (lyrics, chords, guitar tabs etc.) can be found online. Our goal is to come up with ideas/prototypes on how to approach the problem combining existing methods (e.g. vocal activity detection, chord recognition, lyrics-alignment) in new ways, rather than design something completely new. An industry database of vocal cover songs with acoustic accompaniment will be provided.

Georgi is an audio engineer at Smule. He holds a PhD on Music Information Retrieval from the Music Technology Group in Barcelona under the supervision of Xavier Serra. He worked on the topic of automatic alignment of lyrics. He has also experience in applied research on speech recognition and natural language processing. In 2017 he founded VoiceMagix – a company providing solutions for automatic analysis of singing voice.

For several years he is a WiMIR mentor and MIREX task captain.  His research interests are algorithms for the singing voice and speech and machine learning in general. He is currently mainly interested in initiatives aiming at bridging the gap between research in MIR and the music industry.

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Brian McFee:  Coping with Bias in Audio Embeddings

An appealing general approach to modeling problems across many domains is to first transform raw input data through an embedding function, which has been trained on a large (but potentially unrelated) collection of data. This results in a vector representation of each object, which can then be used as input to a simple classifier (e.g., a linear model) to solve some downstream task using a limited amount of data. This approach has been successfully demonstrated in image and video analysis, natural language processing, and is becoming increasingly popular in audio and musical content analysis. However, general-purpose embedding models have been known to encode and propagate implicit biases, which can have detrimental and disparate population-dependent effects.

In this project, we will conduct a preliminary study of embedding bias in MIR data. Using pre-trained audio embeddings and well-known MIR datasets, we will first attempt to quantify the extent to which embedding-based classification exhibits biased results across data sets and/or genres. We will then attempt to de-bias the embedding by adapting recently proposed methods from the natural language processing literature.

Brian McFee is Assistant Professor of Music Technology and Data Science New York University. He received the B.S. degree (2003) in Computer Science from the University of California, Santa Cruz, and M.S. (2008) and Ph.D. (2012) degrees in Computer Science and Engineering from the University of California, San Diego. His work lies at the intersection of machine learning and audio analysis. He is an active open source software developer, and the principal maintainer of the librosa package for audio analysis.


Peter Sobot:  Software Engineering for Machine Learners (and Drummers) – Building Robust Applications with Audio Data  

Building machine learning systems is hard, but building systems that can scale can be even harder. In this workshop, we’ll discuss software engineering techniques to use when building machine learning systems, including methods to make your code easier to write, test, debug, and maintain. We’ll also build an audio sample classifier with these techniques using basic machine learning concepts, and discuss methods for deploying this system at scale. Finally, we’ll take the system to an extreme and use cloud computing to build a system that learns in response to user input.

Peter Sobot is a Staff Engineer at Spotify, where he works on recommendation products at massive scale, including the systems that power Discover Weekly.  His open-source software contributions range from low-level data tools to legendary internet-scale hacks like The Wub MachineHe has spoken at !!Con, Google Cloud Next, and Google Summit, and makes electronic music in his spare time.

Bob Sturm

Bob Sturm: Computer-Guided Analysis of Computer-Generated Music Corpora

Various iterations of the folkrnn system (folkrnn.org) have generated over 100,000 transcriptions of “machine folk”, e.g., https://highnoongmt.wordpress.com/2018/01/05/volumes-1-20-of-folk-rnn-v1-transcriptions/, but manually looking through these takes a lot of time. In this project we will think about and implement some methods that can help one grasp characteristics of such collections, and find interesting bits. For instance, we can look for instances of plagiarism, find anomalous material, judge similarity in terms of pitches, meter, melodic contour, etc.

Bob L. Sturm is currently an Associate Professor in the Speech, Music and Hearing Division of the School of Electronic Engineering and Computer Science at the Royal Institute of Technology KTH, Sweden. Before that he was a Lecturer in Digital Media at the Centre for Digital Music, School of Electronic Engineering and Computer Science, Queen Mary University of London. His research interests include digital signal processing for sound and music signals, machine listening, evaluation, and algorithmic composition. He is also a musician.

Chris Tralie

Chris Tralie: To What Extent Do Cyclic Inconsistencies Exist in Musical Preferences?

Music recommendation algorithms seek to rank a set of candidate songs in order of some estimated user preference.  It may be challenging to ascertain preferences from surveys, however, since Miller’s empirical “rule of 7” could be interpreted to suggest that humans lack the working memory to meaningfully rank much more than 7 items at a time.  To learn a longer list of preferences, then, one could consider presenting only a pair of alternatives at a time and aggregating these pairwise preferences into a global ranking. However, real pairwise rankings can lead to cyclic inconsistencies; that is, people often express that A > B and B > C, but also that C > A.  This is known as the “Condorcet Paradox.” Fortunately, there exists a topological pairwise rank aggregation technique, known as “HodgeRank,”[1] which can aggregate these rankings into the “most consistent” global order, while simultaneously quantifying the degree to which local (A > B > C > A) and global (A > B > C > … > A) exist.  In this workshop, we will first discuss these concepts in more detail, and then we will each listen to pairs of 15 second clips from a diverse corpus of music [2] and rank our preferences, and then apply HodgeRank to see how consistent we all are. We will also use metrics between rankings to show which people in our group have similar preferences.  Zooming out, we will also discuss some social psychology literature that correlates musical preferences to personality traits in music [2], and we will discuss concurrent ethical pitfalls that can emerge when collecting data and interpreting results in such studies.

[1] http://www.ams.org/publicoutreach/feature-column/fc-2012-12

[2] Rentfrow, Peter J., et al. “The song remains the same: A replication and extension of the MUSIC model.” Music Perception: An Interdisciplinary Journal 30.2 (2012): 161-185.

Christopher J. Tralie is a data science researcher working in applied geometry/topology and geometric signal processing. His work spans shape-based music structure analysis and cover song identification, video analysis, multimodal time series analysis, and geometry-aided data visualization. He received a B.S.E. from Princeton University 2011, a master’s at Duke University in 2013, and a Ph.D. in at Duke University in 2017, all in Electrical Engineering. His Ph.D. was primarily supported by an NSF Graduate Fellowship, and his dissertation is entitled “Geometric Multimedia Time Series.”  He then did a postdoc at Duke University in Mathematics and a postdoc at Johns Hopkins University in Complex Systems. He was awarded a Bass Instructional Teaching fellowship at Duke University, and he maintains an active interest in pedagogy and outreach, including longitudinal mentoring of underprivileged youths in STEAM education. He is currently a tenure track assistant professor at Ursinus College in the department of Mathematics and Computer Science. For more info, please visit http://www.ctralie.com.

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TJ Tsai: Generating Music by Superimposing and Adapting Existing Audio Tracks

There has been a lot of work in training models to generate novel music from scratch.  In this workshop, we will explore the possibility of generating music by taking a source audio track and enhancing it by superimposing other segments of existing audio material.  The specific task we will work on is to take a classical piano recording and to overlay techno beats/music in an aesthetically pleasing manner. We will brainstorm different ways to accomplish this task, develop some prototypes, and hopefully generate some new music by the end of the workshop!

Prof. TJ Tsai completed bachelor’s and master’s degrees in electrical engineering at Stanford University.  During college, he studied classical piano with George Barth and participated in the Stanford Jazz Orchestra and the chamber music program.  After graduating, he worked at SoundHound for a few years, and then went to UC Berkeley for his Ph.D. Since 2016 he has been a faculty member in the engineering department at Harvey Mudd College, a STEM-focused liberal arts college in Claremont, CA.

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Gissel Velarde and Andre Holzapfel:  Music Research for Good

In recent years, important advances in artificial intelligence (AI) led to different initiatives considering super-intelligence, its advantages, and dangers. The initiatives fostering beneficial AI include (i) conferences: the AI for Good Global Summit (running since 2017), The Beneficial artificial general intelligence conference (held in 2015, 2017 and 2019), (Iii) the establishment of organizations and projects like OpenAI, Partnership on AI, Google’s AI for Social good, or AI for Humanity from the Université de Montréal, and (iv) governments AI strategies. In last year’s ISMIR conference, our community dedicated a session to discuss ethics in MIR, and there are topics which are still to be addressed. During this workshop, we will review the state of AI for good. We will revisit the tentative ethical guidelines for MIR developers proposed by Holzapfel et. al (2018) and its alignment with guidelines from the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems (Chatila & Havens, 2019), and Ethics Guidelines for Trustworthy AI from the High-Level Expert Group on Artificial Intelligence [HEGAI] (2019).  We will use tools such as SWOAT (strengths, weaknesses, opportunities, and threats) analysis, business canvas, SCAMPER technique for creative thinking and Gantt charts. After a situational analysis, we will define goals, scope, stakeholders, risks, benefits, impact, and an action plan. Finally, we will elaborate ethics guidelines in music research to be proposed to our community for consideration.

Chatila, R., & Havens, J. C. (2019). The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems. In Robotics and Well-Being (pp. 11-16). Springer, Cham.

High-Level Expert Group on Artificial Intelligence (2019). Ethics guidelines for trustworthy AI. Retrieved from https://ec.europa.eu/digital-single-market/en/news/ethics-guidelines-trustworthy-ai

Holzapfel, A., Sturm, B.L. and Coeckelbergh, M., 2018. Ethical Dimensions of Music Information Retrieval Technology. Transactions of the International Society for Music Information Retrieval, 1(1), pp.44–55. DOI: http://doi.org/10.5334/tismir.13

Gissel Velarde is a computer scientist, engineer, pianist and composer. She holds a PhD degree from Aalborg University for her doctoral thesis “Convolutional methods for music analysis” supervised by David Meredith and Tillman Weyde. She participated as a research member of the European project, “Learning to Create” (Lrn2Cre8), a collaborative project within the Future and Emerging Technologies (FET) programme of the Seventh Framework Programme for Research of the European Commission. She was a machine learning lead at Moodagent and worked as a consultant for SONY Computer Science Laboratories.  She is a DAAD alumni and mentor of the WIMIR program.

Andre Holzapfel received M.Sc. and Ph.D. degrees in computer science from the University of Crete, Greece, and a second Ph.D. degree in music from the Centre of Advanced Music Studies (MIAM) in Istanbul, Turkey. He worked at several leading institutes in computer engineering as postdoctoral researcher, with a focus on rhythm analysis in music information retrieval. His field work in ethnomusicology was mainly conducted in Greece, with Cretan dance being the subject of his second dissertation. In 2016, he became Assistant Professor in Media Technology at the KTH Royal Institute of Technology in Stockholm, Sweden. Since then, his research subjects incorporate the computational analysis of human rhythmic behavior by means of sensor technology, and the investigation of ethical aspects of computational approaches to music.

Eva Zangerle

Eva Zangerle – Multi-Dimensional User Models for MIR

In music information retrieval scenarios (particularly, when it comes to personalization), users and their preferences are often modeled solely by their direct interactions with the system (e.g., songs listened to). However, a user’s perception and liking of recommended/retrieved tracks is dependent on a number of dimensions, which may include the (situational) context of the user (e.g., time, location or activity), the user’s intent, content descriptors and characteristics of tracks the users have listened to and also should be able to model the change of preference over time (short vs. long-term). Comprehensive models that capture these multiple dimensions, however, are hardly devised.

In the scope of this workshop, we aim to look into how users and their preferences (long- and short-term) can be modeled, the implications of such comprehensive user models on the underlying MIR algorithms and also, how we can evaluate the contribution and impact of such user models.

Eva Zangerle is a postdoctoral researcher at the University of Innsbruck at the research group for Databases and Information Systems (Department of Computer Science). She earned her master’s degree in Computer Science at the University of Innsbruck and subsequently pursued her Ph.D. from the University of Innsbruck in the field of recommender systems for collaborative social media platforms. Her main research interests are within the fields of social media analysis, recommender systems, and information retrieval. Over the last years, she has combined these three fields of research and investigated context-aware music recommender systems based on data retrieved from social media platforms aiming to exploit new sources of information for recommender systems. She was awarded a Postdoctoral Fellowship for Overseas Researchers from the Japan Society for the Promotion of Science allowing her to make a short-term research stay at the Ritsumeikan University in Kyoto.


WiMIR Workshop 2018: Modeling Repetition and Variation for MIR

Blog post by Iris Yuping Ren, Hendrik Vincent Koops, and Anja Volk.

(Materials are available at https://github.com/hvkoops/wimir2018)

Right after the main ISMIR2018 conference, the WiMIR workshop awaited. As planned, we gathered and formed a working group to tackle the problem of modeling repetition and variation in music for MIR, consisting of the following participants:

Anja Volk (Utrecht University) – Project Guide
Hendrik Vincent Koops (Utrecht University) – Project Guide
Iris Yuping Ren (Utrecht University) – Project Guide
Juan Pablo Bello (New York University)
Eric Nichols (Microsoft)
Jaehun Kim (Delft University)
Marcelo Rodriguez Lopez (Yousician)
Changhong Wang (Queen Mary University of London)
Jing Chen (Nanchang University)
Tejaswinee Kelkar (University of Oslo)

In the morning session, we first reflected on the background of repetitions and variations as central concepts in music observed by musicologists, and then the computational modeling thereof in Music Information Retrieval within different contexts. We discussed that there exists disagreement in annotations in many MIR tasks, such as automatic chord extraction and repeated pattern discovery. Comparable to many other subareas in machine learning and data science, we face complications brought by the unattainability of an absolute, all-encompassing ground truth annotation.

We then provided more detailed motivations and ideas on how to gather annotations on repetitions and variations in music. For example, one set of guidelines was:

Listen to the following pieces and annotate the salient melodic patterns with

  1. How relevant this pattern is to this piece
  2. One word to label the type of this pattern
  3. A short description on why you find it to be a pattern
  4. How difficult it was for you to decide whether it’s a pattern

Using the prepared materials, we had a very active discussion on topics such as: how to define the concepts for specific annotation tasks? How can we use tools such as wearable sensors, a wrist band for example, to help the annotation process?  How can we compare the annotations and annotation methods? (For more, please refer to the github link).

In the afternoon, after a very interesting and useful lunch breakout session, we started with the actual annotation process on the first page of the String Quartet No. 1 in F major, Op. 18, No. 1, Ludwig van Beethoven (1798 and 1800), Violin I. We provided the sheet music, midi and audio files. The participants used different tools to their liking to mark the repetitions and variations on the sheet music. During the annotations, there were already some interesting discussions in some subgroups: how repetitive the young Beethoven was!

In the second part of the afternoon, using the individual annotations, we began our exchange on the experience of the annotation process. We discussed how we can improve on the current designs of annotation processes and tools for annotation tasks, and how the annotated patterns could be used to design an automatic pattern discovery system. We concluded the day with a short presentation.

Throughout the day, we gained many new insights into what are the good and bad ways to create and employ annotations on repetitions and variations. We warmly thank the participants for a great a day of discussions, listening to music, and annotating repetitions and variations!

Iris Yuping Ren is a second year PhD candidate in the Information and Computing Sciences department, Utrecht University, under the supervision of dr. Anja Volk, dr. Wouter Swierstra and dr. Remco C. Veltkamp. She obtained Bachelor degrees in Statistics and Cultural Industry Management from Shandong University, Master degrees in Complex System Science from the University of Warwick and École Polytechnique, Computer and Electrical Engineering in the University of Rochester, and a diploma in violin performance from the Eastman Community Music School. Her current research has a focus on the computational modelling and statistical analysis of musical patterns in various corpora. She is comparing both generic and domain-specific approaches, such as data mining methods, times series analysis, machine learning based clustering and classification algorithms. To discover useful patterns in music, she makes use of functional programming languages to compute pattern transformations and similarity dimensions. Her research contributes to a computationally- and quantitatively-based understanding of music and algorithms. Music wise, she enjoys playing with local orchestra projects and sessions.

Hendrik Vincent Koops is a PhD candidate at Utrecht University under supervision of Dr. Anja Volk and Dr. Remco C. Veltkamp. Vincent holds degrees in Sound Design and Music Composition from the HKU University of the Arts Utrecht, and degrees in Artificial Intelligence from the Utrecht University. After a research internship at Carnegie Mellon University, he started his PhD in Music Information Retrieval. His PhD research concerns the computational modeling of variance in musical harmony. For example, he studied annotator subjectivity to better understand the amount of agreement we can expect among harmony annotators. Using data fusion methods, he investigated how to integrate multiple harmony annotations into a single, improved annotation. For a deep learning study, he created new features for chord-label personalization. Vincent’s research contributes to a better understanding of computational harmony analysis tasks, such as automatic chord estimation. Vincent is also active as a composer for film and small ensembles. Currently, he’s working towards work for a string quartet.

Anja Volk (Utrecht University), holds master degrees in both mathematics and musicology, and a PhD in the field of computational musicology. The results of her research have substantially contributed to areas such as music information retrieval, computational musicology,  music cognition, and mathematical music theory.  In 2016 she launched together with Amélie Anglade, Emilia Gómez and Blair Kaneshiro the Women in MIR (WIMIR) Mentoring Program.  She co-organized the launch of the Transactions of the International Society for Music Information Retrieval, the open access journal of the ISMIR society, and is serving as Editor-in-Chief for the journal’s first term. Anja received the Westerdijk Award 2018 from Utrecht University in recognition of her efforts on increasing diversity.


Start of Peer Mentoring Sign up

For all mentors of the WiMIR mentoring round 2019, we offer Peer Mentoring. In this blog post we would like to familiarize you with the Peer Mentoring sign-up procedure. This year we use Trello (explanations follow below), please note that the sign-up deadline is March 10th.

What is peer mentoring?

Peer mentoring provides mentors with the opportunity to discuss various career aspects with other mentors in the WiMIR program. Peer mentoring is meant to serve as a complement to the traditional mentoring program, in which mentor and mentee in any given pair typically have an unequal amount of experience in the field of MIR. In the case of peer mentoring, the two peers may have comparable amounts of experience, yet benefit from each other by bringing in various perspectives on MIR. For example, these perspectives may differ in terms of scholarly background, geographical affiliation, working environment, MIR subfield of expertise, experience with teaching and public outreach, technical skill set, mentoring practices, and more.

Our hope is that the peer mentoring program will contribute to reinforcing the cohesion of the MIR community at large, and in particular: across countries and continents, across scientific disciplines, and between academia and industry. Furthermore, we aim to frame this program within the core mission of WiMIR, that is, to increase the opportunities of women in the field of MIR. Therefore, we encourage WiMIR mentors of all genders to take part in the peer mentoring program, and adopt this communication channel as a facilitator of diversity and inclusion.

How does peer mentoring work?

The first stage of the peer mentoring program is for you to introduce yourself to the rest of the WiMIR mentors. The second stage is to read the profiles of other participants, rank them by order of preference, and send us the ranked list of your top choices. The third stage, once you are assigned a peer, is for you to connect with them through private electronic communication.

Why use Trello?

Last year, the interface for introducing oneself to other peer mentors, and selecting a peer, was a simple shared spreadsheet on Google Documents. This year, because of the rising number of participants, we have decided to migrate to another interface: Trello. This might seem like an iconoclastic choice given that, for those of you who already know Trello, it is primarily designed to be a tool for task management rather than team building. Yet, as it turns out, the streamlined drag-and-drop interface of a Trello board is actually perfect for us to collect the ranked list of preferences of each participant.

A Trello board consists of items (“cards”) which can be moved from one column (“list”) to another. In project management, cards are tasks and lists are states of completion. However, in our peer mentoring interface, we will be using cards to denote participants, and lists to denote preference. For the time being, there is a single Trello board, and it is only visible to us organizers. We kindly ask participants to fill in this Trello board via an email interface.

In an upcoming stage, we will duplicate this Trello board and send a different, private copy to every one of you. At that point, your role will be to browse through the Trello cards of other participants and rank the ones you want to meet.

How do I introduce myself to other mentors?

You can introduce yourself by creating your Trello card. Rather than giving global access to the entire Trello board, we propose that you use the email-to-board interface of Trello. This interface is lighter, more portable, and more accessible to people with disabilities than the visual interface.

Here is a link describing the email-to-board interface of Trello: https://help.trello.com/article/809-creating-cards-by-email

We particularly point your attention towards the “formatting tips” paragraph.

The subject of the email you will send will become the title of the Trello card.

For consistency, we ask everyone to title their Trello card with three elements, separated by spaces:

  1. The two-letter abbreviation of the country of affiliation
  2. Your full name.
  3. Some hashtags describing your own interests in MIR.

For example:

  • “US Vincent Lostanlen #academia #symbolic #timbre”
  • “NL Vincent Koops #academia #harmony #rhythm”
  • “US Blair Kaneshiro #industry #cognition #performance”
  • etc.

The list of recommended hashtags includes, but is not limited to:

  • #academia
  • #accessibility
  • #behavior
  • #business
  • #careers
  • #cognition
  • #corpora
  • #creation
  • #dance
  • #diversity
  • #ethics
  • #health
  • #indexing
  • #industry
  • #melody
  • #metadata
  • #methodologies
  • #performance
  • #recommendation
  • #rhythm
  • #semantic
  • #structure
  • #symbolic
  • #style
  • #teaching
  • #transcription
  • #timbre
  • #voice

You may include other hashtags in the email subject as you see fit. We highly recommend using the #academia and #industry hashtags, and at least two others in the list.

What to put on my Trello card?

In the email body, we ask mentors to include a small profile to their card that includes some biographical information, research interests, and reasons for wanting to participate in peer mentoring. A recommended outline is

  • Some biographical information
  • Current position(s)
  • Research interests and goals
  • Current research focus
  • Interests and pursuits outside of research
  • Projects you are currently working on
  • Your goals in peer mentoring 

As an example, below is the information on the card of Vincent Lostanlen.

– He/him. 26 years old
– a postdoc at NYU’s Music and Audio Research Lab
– visiting scholar from the Cornell Lab of Ornithology, working on bioacoustics
– research goal: MIR applications at the interaction between signal processing and deep learning
– current focus: contemporary music techniques, timbral and structural similarity
– outside of research: computer music designer for Florian Hecker
– open source: Kymatio, librosa, scattering.m

In addition to scientific topics, I would like to progress in my understanding of diversity and inclusion in MIR, ethical responsibility, and fostering links between research and creation.

I would prefer to establish contacts with peers in France or the UK.

Background: EngD Télécom Paristech 2013, MSc Ircam 2013, PhD applied math ENS 2017.

You can also write in prose if you prefer. Feel free to add as many details about yourself as you want.

What is the email address I should write to?


Again, please make sure that the subject of the email contains your country of affiliation, your full name, and some hashtags of interest.

Deadline: Please make sure you email your Trello card by March 10th.

What if I want to connect with multiple mentors at once?

Although the peer mentoring program is designed to focus on one-to-one communication, we wish to point out that there is also a recommended communication channel for broadcasting messages to all mentors of the WiMIR program. This communication channel is the channel #wimir_mentors_ on the “MIR community” Slack workspace. Below is the link:


Please note, however, that Slack restricts the history of this workspace to the most recent 10,000 messages. Thus, even though this channel is OK for short-lived announcements, it is not ideal for keeping track of the evolution of long-term projects.

Who are the Peer Mentoring Coordinators?

The Peer Mentoring Coordinators will help you find a suitable peer mentor: Hendrik Vincent Koops (Utrecht University) and Vincent Lostanlen (New York University). If you have questions, please contact them at the following email addresses: h.v.koops@gmail.com and vincent.lostanlen@nyu.edu

TL;DR if you are a WiMIR mentor in the 2019 round and want to join the peer mentoring program, please write an email to wimirpeermentors+ardgsv5nleozfdsnxnbx@boards.trello.com

with an email subject of the form “US Vincent Lostanlen #academia #symbolic #timbre” and personal information about yourself in the email body.

With our best wishes,

The Peer Mentoring Coordinators

Hendrik Vincent Koops and Vincent Lostanlen


WiMIR mentoring round 2019 kickoff

The fourth round of the WiMIR mentoring program is about to start,  mentors and mentees have been matched and introduced  to each other by the Mentoring Program Committee.  Participants come from Europe, North and South America,  Oceania and for the first time from Africa. Thanks everyone for contributing and keeping your commitment! Happy mentoring!

WiMIR mentoring 2019 participants

Mentoring Program Committee

  • Johanna Devaney, Brooklyn College, US
  • Ryan Groves, Melodrive, Germany
  • Blair Kaneshiro, Stanford University, US
  • Anja Volk, Utrecht University, the Netherlands

Peer Mentoring Coordinators

  • Hendrik Vincent Koops, Utrecht University, the Netherlands
  • Vincent Lostanlen, New York University, US

Our mentees reside in Australia, Austria, Belgium, Brazil, Denmark, France, Germany, Greece, India, Ireland, Italy, Netherlands, Nigeria, Norway, Singapore, South Korea, Spain, Taiwan, Turkey, United Kingdom, and United States. They represent a diverse field of interests and backgrounds, such as artificial intelligence, signal processing, natural language processing, musicology, applied mathematics, computer science, audio signal processing, psychoacoustics, human computer interactive performance, computational musicology, music perception and cognition, data science, complex system, acoustics, physics, machine learning, software engineering, ethnomusicology, composition, music therapy, neuroscience, and psychology.

We thank our generous mentors from Europe, North and South America, Asia and Oceania for dedicating their time to this program:

Kat Agres, IHPC (A*STAR), Singapore
Steinunn Arnardottir, Native Instruments GmbH, Germany
Thomas Arvanitidis, MUSIC Tribe, United Kingdom
Andreas Arzt, Johannes Kepler University, Austria
Ana M. Barbancho, Universidad de Málaga, Spain
Isabel Barbancho, Universidad de Malaga, Spain
Dogac Basaran, IRCAM, France
Christine Bauer, Johannes Kepler University Linz, Austria
Amy Beeston, University of Leeds, UK (Scotland)
Brian Bemman, Aalborg University, Denmark
Francesco Bigoni, Aalborg University – Copenhagen, Denmark
Rachel Bittner, Spotify, United States
Tom Butcher, Microsoft, USA
Marcelo Caetano, Freelance, Argentina
Mark Cartwright, Apple, UK
Doga Cavdir, CCRMA, Stanford University, United States
JOe Cheri Ross, Linkedin, India
Srikanth Cherla, Jukedeck, Sweden
Orchisama Das, Stanford University (CCRMA), United States
Matthew Davies, INESC TEC, Portugal
Andrew Demetriou, TU Delft, Netherlands
Chris Donahue, UC San Diego, US
Jonathan Driedger, Chordify, Germany/The Netherlands
Andrew Elmsley, Melodrive, Germany
Philippe Esling, IRCAM – Sorbonnes Universités, France
Sebastian Ewert, Waikato University, New Zealand
Ichiro Fujinaga, McGill University, Canada
Fabien Gouyon, Pandora, UK/Portugal
Ryan Groves, Melodrive Inc., Germany
Blair Kaneshiro, Stanford University, USA
Thor Kell, Spotify, United States
Peter Knees, TU Wien, Austria
Hendrik Vincent Koops, Utrecht University, Netherlands
Katerina Kosta, Jukedeck, United Kingdom
Nadine Kroher, MXX Music, Spain
Robin Laney, Open University, UK
Audrey Laplante, Université de Montréal, Canada
Alexander Lerch, Georgia Institute of Technology, USA
Mark Levy, New York University, United States
Michael Mandel, Brooklyn College, CUNY, USA
Ethan Manilow, Northwestern University, USA
Matthew McCallum, Gracenote, United States
Brian McFee, New York University, United States
Blai Meléndez-Catalán, UPF / BMAT, Spain
Gabriel Meseguer Brocal, Ircam, France
Meinard Mueller, International Audio Laboratories Erlangen, Germany
Néstor Nápoles López, McGill University, Canada
Eric Nichols, Microsoft, USA
Oriol Nieto, Pandora, USA
Sergio Oramas, Spotify, United Kingdom
Ritu Patil, Cummins college of engineering, India
Johan Pauwels, Queen Mary University of London, United Kingdom
Marcelo Queiroz, University of São Paulo, Brazil
Elio Quinton, Universal Music Group, United Kingdom
Colin Raffel, Google Brain, USA
Preeti Rao, IIT Bombay, India
Christopher Raphael, Indiana Univ., USA
Justin Salamon, New York University, USA
Andy Sarroff, iZotope, USA
Bertrand Scherrer, LANDR AUDIO INC., Canada
Sertan Şentürk, Pandora, Spain
Amina Shabbeer, Amazon, United States
Ajeet Singh, India
Joren Six, IPEM, Ghent University, Belgium
Jordan Smith, United Kingdom
Mohamed Sordo, Pandora, United States
Ajay Srinivasamurthy, Amazon Alexa, India, India
Bob Sturm, KTH, Sweden
Derek Tingle, IDAGIO, Germany
Christopher Tralie, Duke University, United States
Marcelo Tuller, INESC TEC, Portugal
Doug Turnbull, Ithaca College, United States
Makarand Velankar, MKSSS’S Cummins College of Engineering, Pune, India
Gissel Velarde, Moodagent, Denmark
Christof Weiss, International Audio Laboratories Erlangen, Germany
Chih-Wei Wu, Netflix, Inc., U.S.
Gus Xia, NYU Shanghai, USA/China


WiMIR Workshop 2018: Success!

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We’re pleased to tell you that the WiMIR 1st Annual Workshop was a resounding success!

Why organize a WiMIR Workshop? We saw this as a way to build upon the MIR community’s already strong support for diversity and inclusion in the field. The Workshop format was a fitting complement to the remote pairings of the mentoring program and brief introductions gained during the main ISMIR conference. We proposed three aims for the WiMIR 1st Annual Workshop:

  • Further amplify the scientific efforts of women in the field.
  • Encourage the discussion of proposed or unfinished work.
  • Create additional space for networking.

Thanks to support from Spotify, we were able to offer the WiMIR Workshop as a free event, and open it up to ALL members of the community!  The Workshop took place as a satellite event of ISMIR2018, at Télécom ParisTech. We had 65 pre-registrations, and closer to 80 people attending.  We had poster presentations from 18 women in the field, with topics ranging from Indian Classical music to musical gestures.  We had 11 project groups, ranging from karaoke-at-scale, music for mood modulation, and the relationship between cardiac rhythms & music.  We had a staggering number of croissants and pain au chocolats, too – thanks, Paris.

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The day started with the aforementioned pastries and coffee, and then people joined up with their project groups, introduced themselves, and got a big-picture overview from their Project Guides.  This led into a poster session, focusing on early-stage research ideas.

Posters turned into lunch, which was informally structured around topics like “Dealing with Sexism” and “Surviving Grad School”.  The lunch provided attendees with an opportunity to connect with new people and learn about topics that members in the field (especially those who are not women) don’t often discuss.  

After lunch, the project groups started a deeper dive into their topic areas, with an eye to present at 4 pm.  The presentations were great – we had everything from machine-learned piano melodies to microsurveys about music and emotion to a whole lot of post-it notes about cover songs.

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It was, in general, a lot of fun, and we achieved the aims of the event.  We’re looking forward to next year – it seems like most folks are as well:

It was a fruitful session and our group will certainly continue the work that we started yesterday.” – Elaine Chew, Professor of Digital Media, Queen Mary University

“The most inspiringly diverse event in the field of MIR!” – Oriol Nieto, Senior Scientist, Pandora

“It was exciting to see new diverse groups of people across different backgrounds, disciplines and institutions form new research collaborations!” – Rachel Bittner, Research Scientist, Spotify.

“The first WiMIR Workshop was an amazing way to meet a diverse set of people working in MIR who want to make the world better.  I loved our workshop chats as well as breaking the ice on tougher discussion points during lunch, such as overcoming sexism.  It was staggering to see what each group accomplished in such a short period of time at the first WiMIR Workshop, and I made many great new friendships as well.  Bravo!” – Tom Butcher, Principal Engineering & Science Manager, Microsoft


“I am already looking forward to next year’s!” – Kyungyun Lee, MS student, KAIST

“Very organized, inspiring and motivating event! Excellent way to meet the most welcoming people of the MIR community.” – Bruna Wundervald, PhD Candidate, Maynooth University

“I loved the format! Emerged at the end of the day full of ideas and new motivation.” – Polina Proutskova, Postdoc, Centre for Digital Media, Queen Mary University

And, of course, the tweets:Screen Shot 2018-10-24 at 12.04.49.png

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Big thanks to everyone who helped out: The ISMIR2018 volunteers & General Chairs, the ISMIR Board, WIMIR leadership, Télécom ParisTech, and Emile Marx from Spotify Paris.  

We’ll see you next year in Delft!

The WiMIR Workshop Organizers,


Sign-ups open for WiMIR mentoring round 2019

For preparing the fourth round of the Women in Music Information Retrieval (WiMIR) mentoring program, to begin in January 2019,  we kindly invite previous and new mentors and mentees to sign up  through the following signup forms:

Sign up to GET a mentor in 2019 here: http://bit.ly/2Ns8ulj

Sign up to BE a mentor in 2019 here: http://bit.ly/2Da6ZTZ

Signups close Nov 30, 2018. Mentor/mentee matches will be announced in January 2019.

The WiMIR mentoring program connects women students, postdocs, early-stage researchers, industry employees, and faculty to more senior women and men in MIR who are dedicated to increasing opportunities for women in the field. Mentors will share their experiences and offer guidance to support mentees in achieving and exceeding their goals and aspirations. The program offers to all mentors the option to pair up with a peer mentor for discussing relevant topics with a professional at a similar stage of their career.  By connecting individuals of different backgrounds and expertise, this program strengthens networks within the MIR community, both in academia and industry. 

Time commitment: four remote meetings between January and end of June 2019.

Who is eligible?

– Female undergraduates, graduate students, postdocs, early-stage researchers, industry employees, and faculty may sign up as mentees. 

– Graduate students, industry employees, researchers, and faculty of any gender may sign up as mentors. 

– Those meeting criteria for both mentor and mentee roles are welcome to sign up as both. 

Faculty: Please share this announcement with female undergraduates in your departments and labs who may be interested in participating. The mentoring program can help attracting newcomers at an early stage to the MIR field.

More information on the program

General information: https://wimir.wordpress.com/mentoring-program/ 

Report on the mentoring round in 2017:  http://bit.ly/2yuWS5i

Report on the mentoring round in 2018:  https://bit.ly/2P5pBG3

Questions? Email wimir-mentoring@ismir.net 

We look forward to your response and commitment to continuing the mentoring program!

The WiMIR Mentoring Program Committee

Johanna Devaney, Ryan Groves, Blair Kaneshiro, and Anja Volk


WiMIR Mentoring Program Report 2018: On the “only meeting that should last longer”


Poster design: Julia Wilkins

Blog post by Anja Volk (Utrecht University), Co-Founder of the WiMIR Mentoring Program

“This is the only hour-long meeting on my calendar that I secretly wish would last longer.” Let’s take this quote from a mentor’s anonymous feedback on his/her experience with the WiMIR mentoring program as the opening fanfare to our report on the outcomes of the 2018 mentoring round as reflected by the participants. I can hardly think of any bigger compliment to this program from the perspective of a busy mentor. Before looking into what other mentors and mentees told us in their anonymous feedback about their experience with the program, allow me some remarks on reports in the field of Music Information Retrieval.

We love big numbers in Music Information Retrieval – we are fans of analyzing millions of musical pieces and reporting statistics. Accordingly, our report on the WiMIR mentoring round in 2018 might deal with a lot of numbers, such as the fact that the number of participants has doubled again as in previous years, with 80 mentor-mentee pairs enrolling this time, while participants came from Europe, North and South America, Asia and Oceania. Or we might count how the list of academic institutions participating has only grown since the first round in 2016, with about 70 institutions participating in 2018,  and that we have meanwhile mentors from most of the leading music technology companies and even AI and music startups, adding up to about 40 companies. You can check that out here.

However, let’s take in this report the musicologist’s approach of giving great care to details, analyzing one piece after the other (and not necessarily millions at once) and let’s listen to one piece at a time, or better to one story at a time on how the mentees felt empowered, gained career perspectives, came to appreciate the MIR community and felt encouraged and included through the mentoring sessions. These individual stories might give a more detailed picture on what has been gained than plain numbers.

For a description of the general format of the WiMIR mentoring program, with 4 remote meetings between mentor and mentee, you can check out last year’s report here

Exposition first theme

Outcomes from mentoring sessions on career perspectives as reported by mentees

The following anonymous quotes provide an overview of how mentees were able to gain clarities and perspectives on their career options in MIR.

Not only has the WiMIR mentoring programme opened up opportunities for me to study it and work abroad, experiencing other universities, it has built my confidence with networking with more senior academics.

I already told this to anyone I met working in wide ranged related fields. This is the best way to find your path to learn or make career goals.

With his guidance, I found my path through my best interests in both academic and industrial ways.

I have more clarity on my career path.

Discussing with a successful woman in this field was very interesting so that I could ask specific questions about my work/life path that would help me making decisions for my future career.

It deepened my understanding on research from the perspective of a big picture.

The program provides an important channel for research and career information exchange, which means a lot for early-stage researchers.

Sign up for the WiMIR mentoring programme because TRUST ME you will NOT regret it. It’s the best thing I have done for my future within my PhD.

Exposition second theme

Specific outcomes from mentoring sessions on career perspectives as reported by mentees

Quite a range of different projects have emerged from the mentoring sessions this year, from landing a job to programming skills, writing CVs, papers or research proposals, or getting an internship. Here are some examples.

I got a new job in the industry that relates to music! My mentor helped with all of the positive support and encouragement!

So, thanks to my mentor, I applied to the WiMIR Grant Application at the ISMIR Conference 2018.

I was able to land a job that combines music and computer science and I’m really excited to be making a difference in the music world from a variety of areas!

I received valuable feedback on my job materials such as my CV and a cover letter.

I learnt handy programming tricks.

I wrote and submitted a fellowship application (which got through to the final shortlist for the award).

I’ve learnt how to define and narrow a research problem and how to solve it step by step.

We could come up with a collaborative work on which we are currently working.

I presented a paper that I was working on for feedback to students/ faculty at University X.

I finally created a personal website.

Received help with a conference proposal and acceptance for conference.

Time saving! Great to have someone to help make yes/no decisions about whether opportunities are worth chasing or not.

Received help shaping my dissertation topic.

Started collaborating for a new paper.


Encouragement, encouragement, encouragement

An underlying topic that recurs over the editions of the mentoring program since 2016 is that of encouragement for mentees. Why is that so important? The psychiatrist Anna Fels has shown that ambition is built on two components: 1) mastering a skill, and 2) being recognized for it. Fels has demonstrated that being recognized by others for their skills happens to a much smaller extent for girls and women than for boys and men: “The personal and societal recognition they receive for their accomplishments is quantitatively poorer, qualitatively more ambivalent, and, perhaps most discouraging, less predictable.” Unfortunately, this starts already early for girls at schools: “Despite the fact that girls’ and women’s achievements, particularly in the academic sphere, frequently outstrip those of their male peers, they routinely underestimate their abilities. Boys and men, by contrast, have repeatedly been shown to have an inflated estimation of their capabilities. Paradoxically, these inaccurate self-ratings by both women and men seem to be accurate reflections of the praise and recognition they receive for their efforts. The impact of these findings on the selection and pursuit of an ambition is obvious: If you don’t think the chances are great that you will reach a career goal, you won’t attempt to reach it—even if the rewards are highly desirable.” (quotes from Anna Fels’ Harvard Business Review “Do Women Lack Ambition?”) More and more empirical studies reveal the different contexts in which women receive less recognition for the same skills as their male peers, such as the study by Moss-Racusin et al. (2012) which has shown that both male and female faculty rated male applicants as significantly more competent than women with identical application materials, and a study by Reuben et al. (2014) showing that both men and women were twice as likely to hire a man for a job that required math than a woman for that same job, even though the women performed equally well in an arithmetic test. Seeing, recognizing and rewarding the skills and talents of women seems to be an important ingredient to learn for all of us.

The WiMIR mentors pay an invaluable contribution toward encouraging mentees to follow their ambitions by doing exactly this: Seeing and recognizing their talents, showing possible career paths,  giving positive feedback on the mentees’ talents, and coming up with concrete steps such as those we have listed above in the exposition. At the same time, mentoring is a great way to discover female talent, and hence a big gain for the MIR community in getting to know these talented women and keep them hopefully involved in the field. Here are some mentees’ reflections on the encouragement this produces:

I have had one of the well-known, experienced MIR researchers all for myself – to talk about myself and help me set goals and develop a vision – what a luxury! I have emerged after my PhD without any understanding what I should do and where the field is going. I felt frustrated and disorientated and the positive, supportive attitude of my mentor was reassuring. Since then I have been on a journey of self-discovery and motivation and I am sure my mentor would be able to help me on several stages of this journey.

… helpful to talk to someone who has followed a career path that is similar to the one I plan to follow, and about which I had many doubts and fears.

I gained a mentor who has empowered me immensely.

I believe that the most important gain from the program was more confidence to work with MIR.

Now I could imagine myself researching interesting and relevant topics and going further in the academic carrier.

I became more optimistic as a Ph.D. student and have new insights to look at my research. The encouragements from my mentor mean a lot to me.

It encouraged me to try to stay in our field.

I felt empowered to ask questions openly and honestly, and felt like my mentor wanted to participate in our conversations just as much as I did. I felt valued and heard during our meetings.

It has opened so many doors for me, and built my confidence in networking in a competitive community.

The WiMIR mentoring has empowered myself.

Women in STEM are often unsure if it is okay to simultaneously feel assertive and vulnerable.  I was given the opportunity to ask questions and provide my own thoughts about STEM, MIR and other topics in a way that felt heard, respected and valued.  I got to practice asking questions in an open and trusting manner, which ultimately led me to understand that honesty, transparency and assertiveness (even in asserting that you are very confused and unsure about something) actually provide a platform for empowerment, respect and growth.

The programme shows you that you are not alone in MIR and STEM. Women are a minority, and this programme brings us together, it inspires and develops us as individuals and as a whole group. I feel that the programme brings confidence to new and aspiring researchers in the field, showing how we can get to the places we wish to reach.

Recapitulation first theme

Beyond the individual – effects of the program on the MIR community

One-on-one meetings in the mentoring program produce ripples beyond the individuals; they contribute to how the MIR community is perceived as a whole, as the following examples show:

I realized that the MIR community is wide, respectful and open to new members, even if they come from related but slightly different research domains.

If I had not applied for the WiMIR Mentoring Program, I probably wouldn’t know the amazing things that could be made from Music. This is the first place that I recommend to start learning and networking in the Music and Technology field.

MIR is a new field for me, but because WiMIR is here, I didn’t have to be scared to be a minority in a STEM field and MIR.

This is an important project to encourage new researchers to be in contact with important professionals and to develop new ideas. For women it is an opportunity to be visible and make more relevant works. I am very grateful for the excellent work of you organizers and I hope to meet you all at ISMIR 2018! =)

I’m really grateful to be attached to the community in this way even though I cannot yet make it to meetings in person. Thank you!

Because it was so easy to discuss things with my mentor, I found it easier to ask a question to other senior members of the MIR community.

Women have so many great ideas, and they bring different methods, perspectives and communication strategies to the table.  The more the women understand they are welcome and needed in MIR, the more they will stick around and be willing to dig deep.

If you don’t want to get lost in many keywords, this program will make you find your learning/career path.

Got to learn a lot from my mentor who is already established in this field. I also got referred to other people and got their feedback and guidance too.

Recapitulation second theme

The gain for mentors

The mentoring program is not only a gain for mentees; perhaps equally important are the gains for mentors. Here are some examples.

It’s really nice to interact with someone who is earlier in her career, and still has very many options to choose from and is also excited about them all. It’s easy to get lost in the day-to-day and forget why I’m doing what I do.

It made me be self-reflective in good ways.

Learning more about academic career paths in different cultures.

I wasn’t expecting to learn so much about recruiters, and the wide variety and competition of the job market.

The issues that women face are fundamentally different, even when they involve exactly the same scenario, just because of the way women are perceived in the workplace. I find that sometimes the approaches I might take as a man simply wouldn’t work for a woman, and it reveals that there is some underlying imbalance there.

It definitely makes me more aware of the gender imbalances and helps me refocus on efforts working with female students at my own institution.

The program helps me in reflecting my one role as an academic advisor.

I realised that all the prejudices that I need to deal with as a musicologist working with engineers are very similar to those an engineer had to face when working with musicologists.

Learned more on research cultures in other labs.

It was great to exchange ideas, links to reading material and perspectives. Hearing how people work in other companies and in academia was very interesting. Both my experience as a mentor and being involved in peer-mentoring were extremely eye opening.

… also learnt a lot about the challenges of raising a family and balancing that with work aspirations.

… learnt more about US universities, her industry experiences.

… a different perspective; insight into a different MIR subfield.

… a window into a different university system (in the USA).

I learned how to share industry experience with grads students.

… learning how to approach people who communicate differently.

I learned more about the obstacles of especially young females. We talked a lot about the many inappropriate statements by male colleagues and other people outside the work context.

It’s unfortunately common for women to encounter hostility and bias. Being a mentor can help balance the experience by demonstrating that not everyone has a negative attitude.


Future directions

Participants in the mentoring program came up with suggestions for further directions of the WiMIR initiative in their feedback forms, such as asking everyone to take the Harvard implicit associations test, asking industry sponsors to highlight their career paths for future female employees, having women-focused industry job fairs or network development, creating  videos about WiMIR, such as testimonial videos about the WiMIR Mentoring program and upload them on YouTube so many women can watch and learn about it and having more local meetups of mentees and mentors. We will discuss these ideas during the WiMIR session at ISMIR 2018 – and will need help realizing them!

Coda with closing fanfare

Fun for everybody involved in the program receiving praise in the feedback forms. Thanks everybody!

Running the mentoring program requires the dedication and time of the mentoring program committee, the mentors and the mentees. For most people, this is time spent on top of many other agenda points in a busy week. We hope the following quotes show to everybody how impactfully and meaningfully this time was spent, which brings us full circle to the opening fanfare of this report on the one hour-meeting that should have lasted longer.  

That was excellent. I will never forget this experience.

It was an excellent experience.

WiMIR Mentoring Program is So Awesome!

Awesome program!!

Just to say that I really enjoyed it, and I think it’s a fantastic initiative.

It was a good experience!

This is a great initiative, keep up the good work.

Love it. Thanks for making a cool program!

I would really like to thank WiMIR organizers for all the great work resulting in significant change in the field.

This mentorship program is one of the most effective ways to diversify the field of MIR, I hope this goes on for many years to come!

Thanks to the WiMIR team for the great concept and organizing this very impactful initiative.

Anja Volk (Utrecht University), holds master degrees in both mathematics and musicology, and a PhD in the field of computational musicology. The results of her research have substantially contributed to areas such as music information retrieval, computational musicology,  music cognition, and mathematical music theory.  In 2016 she launched together with Amélie Anglade, Emilia Gómez and Blair Kaneshiro the Women in MIR (WIMIR) Mentoring Program.  She co-organized the launch of the Transactions of the International Society for Music Information Retrieval, the open access journal of the ISMIR society, and is serving as Editor-in-Chief for the journal’s first term. Anja received the Westerdijk Award 2018 from Utrecht University in recognition of her efforts on increasing diversity.


Anja Volk awarded this year’s Westerdijk Award

Blog post written by Vincent Koops. 
Dr. Anja Volk, one of WiMIR leading scholars, is awarded this year’s Westerdijk Award at the Utrecht University in recognition of her efforts to create a more diverse organization. Besides her efforts in building the WiMIR network, she established the Women in Information and Computing Science network. This network is very active in organizing events that stimulate more diversity and inclusion within the department and in applying for funding to finance these events. Anja is furthermore a major contributor to develop concrete recommendations for more diverse leadership within her department. Anja is deeply appreciated because of her passionate efforts to improve diversity and inclusion within and beyond Utrecht University!
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You can read the complete news here: https://www.uu.nl/en/news/anja-volk-wins-westerdijk-award

WiMIR Workshop 2018 Project Guides

This is a list of project guides and their areas of interest for the 2018 WiMIR workshop.  These folks will be leading the prototyping and early research investigations at the workshop.  You can read about them and their work in detail below, and sign up to attend the WiMIR workshop here.



Rachel Bittner:  MIR with Stems

The majority of digital audio exists as mono or stereo mixtures, and because of this MIR research has largely focused on estimating musical information (beats, chords, melody, etc.) from these polyphonic mixtures. However, stems (the individual components of a mixture) are becoming an increasingly common audio format. This project focuses on how MIR techniques could be adapted if stems were available for all music. Which MIR problems suddenly become more important? What information – that was previously difficult to estimate from mixtures – is now simple to estimate? What new questions can we ask about music that we couldn’t before? As part the project, we will try to answer some of these questions and create demos that demonstrate our hypotheses.

Rachel is a Research Scientist at Spotify in New York City, and recently completed her Ph.D. at the Music and Audio Research Lab at New York University under Dr. Juan P. Bello. Previously, she was a research assistant at NASA Ames Research Center working with Durand Begault in the Advanced Controls and Displays Laboratory. She did her master’s degree in math at NYU’s Courant Institute, and her bachelor’s degree in music performance and math at UC 2 Irvine. Her research interests are at the intersection of audio signal processing and machine learning, applied to musical audio. Her dissertation work applied machine learning to various types of fundamental frequency estimation.

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Tom Butcher: Expanding the Human Impact of MIR with Mixed Reality

Mixed reality has the potential to transform our relationship with music. In this workshop, we will survey the new capabilities mixed reality affords as a new computing paradigm and explore how these new affordances can open the world of musical creation, curation, and enjoyment to new vistas. We will begin by discussing what mixed reality means, from sensors and hardware to engines and platforms for mixed reality experiences. From there, we will discuss how mixed reality can be applied to MIR- related fields of study and applications, considering some of the unique challenges and new research questions posed by the technology. Finally, we will discuss human factors and how mixed reality coupled with MIR can lead to greater understanding, empathy, expression, enjoyment, and fulfillment.

Tom Butcher leads a team of engineers applied scientists in Microsoft’s Cloud & AI division focusing on audio sensing, machine listening, avatars, and applications of AI. In the technology realm, Tom is an award-winning creator of audio and music services, which include recommendation engines, continuous playlist systems, assisted composition agents, and other tools for creativity and productivity. Motivated by a deep enthusiasm for synthesizers and electronic sounds from an early age, Tom has released many pieces of original music as Orqid and Codebase and continues to record and perform. In 2015, Tom co- founded a Seattle-based business focusing on community, education, and retail for synthesizers and electronic music instruments called Patchwerks.


Elaine Chew: MIR Rhythm Analysis Techniques for Arrhythmia ECG Sequences

Cardiac arrhythmia has been credited as the source of the dotted rhythm at the beginning of Beethoven’s “Adieux” Sonata (Op.81a) (Goldberger, Whiting, Howell 2014); the authors have also ascribed Beethoven’s “Cavatina” (Op.130) and another piano sonata (Op.110) to his possible arrhythmia. It is arguably problematic and controversial to diagnose arrhythmia in a long-dead composer through his music. Without making any hypothesis on composers’ cardiac conditions, Chew (2018) linked the rhythms of trigeminy (a ventricular arrhythmia) to the Viennese Waltz and scored atrial fibrillation rhythms to mixed meters, Bach’s Siciliano, and the tango; she also made collaborative compositions (Chew et al. 2017-8) from longer ventricular tachycardia sequences. Given the established links between heart and musical rhythms, in this workshop, we shall take the pragmatic and prosaic approach of applying a wide variety of MIR rhythm analysis techniques to ECG recordings of cardiac arrhythmias, exploring the limits of what is currently possible.

Chew, E. (2018). Notating Disfluencies and Temporal Deviations in Music and Arrhythmia. Music and Science. [ html | pdf ]
Chew, E., A. Krishna, D. Soberanes, M. Ybarra, M. Orini, P. Lambiase (2017-8). Arrhythmia Suitebit.ly/heart-music-recordings
Goldberger, Z. D., S. M. Whiting, J. D. Howell (2014). The Heartfelt Music of Ludwig van Beethoven. Perspectives in Biology and Medicine, 57(2): 285-294. [synopsis]

Elaine Chew is Professor of Digital Media at Queen Mary University of London, where she is affiliated with the Centre for Digital Music in the School of Electronic Engineering and Computer Science. She was awarded a 2018 ERC ADG for the project COSMOS: Computational Shaping and Modeling of Musical Structures, and is recipient of a 2005 Presidential Early Career Award in Science and Engineering / NSF CAREER Award, and 2007/2017 Fellowships at Harvard’s Radcliffe Institute for Advanced Studies. Her research, which centers on computational analysis of music structures in performed music, performed speech, and cardiac arrhythmias, has been supported by the ERC, EPSRC, AHRC, and NSF, and featured on BBC World Service/Radio 3, Smithsonian Magazine, Philadelphia Inquirer, Wired Blog, MIT Technology Review, etc. She has authored numerous articles and a Springer monograph (Mathematical and Computational Modeling of Tonality: Theory and Applications), and served on the ISMIR steering committee.



Johanna Devaney:  Cover Songs for Musical Performance Comparison and Musical Style Transfer

Cover versions of a song typically retain basic musical the material of the song being covered but may vary a great deal in their fidelity to other aspects of the original recording. While some covers only differ in minor ways, such as timing and dynamics, while others may use completely different instrumentation, performance techniques, or genre. This workshop will explore the potential of cover songs for studying musical performance and for performing musical style transfer. In contrast to making comparisons between different performances of different songs, cover songs provide a unique opportunity to evaluate differences in musical performance, both within and across genres. For musical style transfer, the stability of the musical material serves as an invariant representation, which allows for paired examples for training machine learning algorithms. The workshop will consider issues in dataset creation as well as metrics for evaluating performance similarity and style transfer.

Johanna is an Assistant Professor of Music Technology at Brooklyn College, City University of New York and the speciality chief editor for the Digital Musicology section of Frontiers in Digital Humanities. Previously she taught in the Music Technology program at NYU Steinhardt and the Music Theory and Cognition program at Ohio State University. Johanna completed her post-doc at the Center for New Music and Audio Technologies (CNMAT) at the University of California at Berkeley and her PhD in music technology at the Schulich School of Music of McGill University. She also holds an MPhil degree in music theory from Columbia University, as well as an MA in composition from York University in Toronto. Johanna’s research seeks to understand how humans engage with music, primarily through performance, with a particular focus on intonation in the singing voice, and how computers can be used to model and augment our understanding of this engagement.


DougEck (1).jpg

Doug Eck: Building Collaborations Among Artists, Coders and Machine Learning

We propose to talk about challenges and future directions for building collaborations among artists, coders and machine learning researchers. The starting point is g.co/magenta. We’ve learned a lot about what works and (more importantly) what doesn’t work in building bridges across these areas. We’ll explore community building, UX/HCI issues, research directions, open source advocacy and the more general question of deciding what to focus on in such an open-ended, ill-defined domain. We hope that the session is useful even for people who don’t know of or don’t care about Magenta. In other words, we’ll use Magenta as a starting point for exploring these issues, but we don’t need to focus solely on that project.

Douglas Eck is a Principal Research Scientist at Google working in the areas of music, art and machine learning. Currently he is leading the Magenta Project, a Google Brain effort to generate music, video, images and text using deep learning and reinforcement learning. One of the primary goals of Magenta is to better understand how machine learning algorithms can learn to produce more compelling media based on feedback from artists, musicians and consumers. Before focusing on generative models for media, Doug worked in areas such as rhythm and meter perception, aspects of music performance, machine learning for large audio datasets and music recommendation for Google Play Music. He completed his PhD in Computer Science and Cognitive Science at Indiana University in 2000 and went on to a postdoctoral fellowship with Juergen Schmidhuber at IDSIA in Lugano Switzerland. Before joining Google in 2010, Doug worked in Computer Science at the University of Montreal (MILA machine learning lab) where he became Associate Professor.



Ryan Groves:  Discovering Emotion from Musical Segments

In this project, we’ll first survey the existing literature for research on detecting emotions from musical audio, and find relevant software tools and datasets to assist in the process. Then, we’ll try to formalize our own expertise in how musical emotion might be perceived, elicited and automatically evaluated from musical audio. The goal of the project will be to create a software service or tool that can take a musical audio segment that is shorter than a whole song, and detect the emotion from it.

Ryan Groves is an award-winning music researcher and veteran developer of intelligent music systems. He did a Masters’ in Music Technology at McGill University under Ichiro Fujinaga, has published in conference proceedings including Mathematics and Computation in Music, Musical Metacreation (ICCC & AIIDE), and ISMIR. In 2016, he won the Best Paper award at ISMIR for his paper on “Automatic melodic reduction using a supervised probabilistic context-free grammar”.  He is currently the President and Chief Product Officer at Melodrive – an adaptive music generation system. Using cutting-edge artificial intelligence techniques, Melodrive allows any developer to automatically create and integrate a musical soundtrack into their game, virtual world or augmented reality system.  With a strong technical background, extensive industry experience in R&D, and solid research footing in academia, Ryan is focused on delivering innovative and robust musical products.



Christine Ho, Oriol Nieto, & Kristi Schneck:  Large-scale Karaoke Song Detection

We propose to investigate the problem of automatically identifying Karaoke tracks in a large music catalog. Karaoke songs are typically instrumental renditions of popular tracks, often including backing vocals in the mix, such that a live performer can sing on top of them. The automatic identification of such tracks would not only benefit the curation of large collections, but also its navigation and exploration. We challenge the participants to think about the type of classifiers we could use in this problem, what features would be ideal, and what dataset would be beneficial to the community to potentially propose this as a novel MIREX (MIR Evaluation eXchange) task in the near future.

Oriol Nieto is a Senior Scientist at Pandora. Prior to that, he defended his Ph.D Dissertation in the Music and Audio Research Lab at NYU focusing on the automatic analysis of structure in music. He holds an M.A. in Music, Science and Technology from the Center for Computer Research in Music and Acoustics at Stanford University, an M.S. in Information Theories from the Music Technology Group at Pompeu Fabra University, and a Bachelor’s degree in Computer Science from the Polytechnic University of Catalonia. His research focuses on music information retrieval, large scale recommendation systems, and machine learning with especial emphasis on deep architectures. Oriol plays guitar, violin, and sings (and screams) in his spare time.

Kristi Schneck is a Senior Scientist at Pandora, where she is leading several science initiatives on Pandora’s next-generation podcast recommendation system. She has driven the science work for a variety of applications, including concert recommendations and content management systems. Kristi holds a PhD in physics from Stanford University and dual bachelors degrees in physics and music from MIT.

Christine Ho is a scientist on Pandora’s content science team, where she works on detecting music spam and helps teams with designing their AB experiments. Before joining Pandora, she completed her PhD in Statistics at University of California, Berkeley and interned at Veracyte, a company focused on applying machine learning to genomic data to improve outcomes for patients with hard-to-diagnose diseases.


Xiao Hu: MIR for Mood Modulation: A Multidisciplinary Research Agenda

Mood modulation is a main reason behind people’s engagement with music, whereas how people use music to modulate mood and how MIR techniques and systems can facilitate this process continue fascinating researchers in various related fields. In this workshop group, we will discuss how MIR researchers with diverse backgrounds and interests can participate in this broad direction of research. Engaging activities are designed to enable hands-on practice on multiple research methods and study design (both qualitative and quantitative/computational). Through feedback from peers and the project guide, participants are expected to start developing a focused research agenda with theoretical, methodological and practical significance, based on their own strengths and interests. Participants from different disciplines and levels are all welcomed. Depending on the background and interests of the participants, a small new dataset is prepared for fast prototyping on how MIR techniques and tools can help enhancing this multidisciplinary research agenda.

Dr. Xiao Hu has been studying music mood recognition and MIR evaluation since 2006. Her research on affective interactions between music and users has been funded by the National Science Foundation of China and Research Grant Council (RGC) of the Hong Kong S. A. R. Dr. Hu was a tutorial speaker in ISMIR conferences in 2012 and 2016. Her papers have won several awards in international conferences and have been cited extensively. She has served as a conference co-chair (2014), a program co-chair (2017 and 2018) for ISMIR, and an editorial board member of TISMIR. She was in the Board of Directors of ISMIR from 2012 to 2017. Dr. Hu has a multidisciplinary background, holding a PhD degree in Library and Information Science, Multi-disciplinary Certificate in Language and Speech Processing, and a Master’s degree in Computer Science, a Master’s degree in Electrical Engineering and a Bachelor’s degree in Electronics and Information Systems.

Anja Volk, Iris Yuping Ren, & Hendrik Vincent Koops:  Modeling Repetition and Variation for MIR

Repetition and variation are fundamental principles in music. Accordingly, many MIR tasks are based on automatically detecting repeating units in music, such as repeating time intervals that establish the beat, repeating segments in pop songs that establish the chorus, or repeating patterns that constitute the most characteristic part of a composition. In many cases, repetitions are not literal, but subject to slight variations, which introduces the challenge as to what types of variation of a musical unit can be reasonably considered as a re-occurrence of this unit. In this project we look into the computational modelling of rhythmic, melodic, and harmonic units, and the challenge of evaluating state-of-the-art computational models by comparing the output to human annotations. Specifically, we investigate for the MIR tasks of 1) automatic chord extraction from audio, and 2) repeated pattern discovery from symbolic data, how to gain high-quality human annotations which account for different plausible interpretations of complex musical units. In this workshop we discuss different strategies of instructing annotators and undertake case studies on annotating patterns and chords on small data sets. We compare different annotations, jointly reflect on the rationales regarding these annotations, develop novel ideas on how to setup annotation tasks and discuss the implications for the computational modelling of these musical units for MIR.

Anja Volk holds masters degrees in both Mathematics and Musicology, and a PhD from Humboldt University Berlin, Germany. Her area of specialization is the development and application of computational and mathematical models for music research. The results of her research have substantially contributed to areas such as music information retrieval, computational musicology, digital cultural heritage, music cognition, and mathematical music theory. In 2003 she has been awarded a Postdoctoral Fellowship Award at the University of Southern California, in 2006 she joined Utrecht University as a Postdoc in the area of Music Information Retrieval. In 2010 she has been awarded a highly prestigious NWO-VIDI grant from the Netherlands Organisation for Scientific Research, which allowed her to start her own research group. In 2016 she co-launched the international Women in MIR mentoring program, in 2017 she co-organized the launch of the Transactions of the International Society for Music Information Retrieval, and is serving as Editor-in-Chief for the journal’s first term.

Cynthia C. S. Liem & Andrew Demetriou:  Beyond the Fun: Can Music We Do Not Actively Like Still Have Personal Significance?

In today’s digital information society,music is typically perceived and framed as ‘mere entertainment’. However, historically, the significance of music to human practitioners and listeners has been much broader and more profound. Music has been used to emphasize social status, to express praise or protest, to accompany shared social experiences and activities, and to moderate activity, mood and self-established identity as a ‘technology of the self’. Yet today, our present-day music services (and their underlying Music Information Retrieval (MIR) technology) do not focus explicitly on fostering these broader effects: they may be hidden in existing user interaction data, but this data usually lacks sufficient context to tell for sure.  As a controversial thought, music that is appropriate for the scenarios above may not necessarily need to be our favorite music, yet still be of considerable personal value and significance to us. How can and should we deal with this in the context of MIR and recommendation? May MIR systems then become the tools that can surface such items, and thus create better user experiences that users could not have imagined themselves? What ethical and methodological considerations should we take into account when pursuing this? And, for technologists in need of quantifiable and measurable criteria of success, how should the impact of suggested items on users be measured in these types of scenarios?   In this workshop, we will focus on discussing these questions from an interdisciplinary perspective, and jointly designing corresponding initial MIR experimental setups.

Cynthia Liem graduated in Computer Science at Delft University of Technology, and in Classical Piano Performance at the Royal Conservatoire in The Hague. Now an Assistant Professor at the Multimedia Computing Group of Delft University of Technology, her research focuses on music and multimedia search and recommendation, with special interest in fostering the discovery of content which is not trivially on users’ radars. She gained industrial experience at Bell Labs Netherlands, Philips Research and Google, was a recipient of multiple scholarships and awards (e.g. Lucent Global Science & Google Anita Borg Europe Memorial scholarships, Google European Doctoral Fellowship, NWO Veni) and is a 2018 Researcher-in-Residence at the National Library of The Netherlands. Always interested in discussion across disciplines, she also is co-editor of the Multidisciplinary Column of the ACM SIGMM Records. As a musician, she still has an active performing career, particularly with the (inter)nationally award-winning Magma Duo.

Andrew Demetriou is currently a PhD candidate in the Multimedia Computing Group at the Technical University at Delft. His academic interests lie in the intersection of the psychological and biological sciences, and the relevant data sciences, and furthering our understanding of 1) love, relationships, and social bonding, and 2) optimal, ego-dissolutive, and meditative mental states, 3) by studying people performing, rehearsing, and listening to music. His prior experience includes: assessing the relationship between initial romantic attraction and hormonal assays (saliva and hair) during speed-dating events, validating new classes of experimental criminology VR paradigms using electrocardiography data collected both in a lab and in a wild setting (Lowlands music festival), and syntheses of musical psychology literature which were presented at ISMIR 2016 and 2017.



Matt McVicar: Creative applications of MIR Data

In this workshop, you’ll explore the possibility of building creative tools using MIR data. You’ll discuss the abundance of prevailing data for creative applications, which in the context of this workshop simply means “a human making something musical”. You, as a team, may come up with new product or research ideas based on your own backgrounds, or you may develop an existing idea from existing products or research papers. You may find that the data for your application exists already, so that you can spend the time in the workshop fleshing out the details of how your application will work. Else, you may discover that the data for your task does not exist, in which case you, as a team, could start gathering or planning the gathering of these data.

Matt is Head of Research at Jukedeck. He began his PhD at the University of Bristol under the supervision of Tijl De Bie and finished it whilst on a Fulbright Scholarship at Columbia University in the city of New York with Dan Ellis. He then went on to work under Masataka Goto at the National Institute for Advanced Industrial Science and Technology in Tsukuba, Japan. Subsequently, he returned to Bristol to undertake a 2 year grant in Bristol. He joined Jukedeck in April 2016, and his main interests are the creative applications of MIR to domains such as algorithmic composition.



WiMIR 1st Annual Workshop


WiMIR 1st Annual Workshop

WiMIR is excited to partner with Spotify to offer the first-ever WiMIR Workshop, taking place on Friday, 28 September 2018 at Télécom ParisTech in Paris, France. This event is open to all members of the MIR community.

The goal of this event is to provide a venue for mentorship, networking, and collaboration among women and allies in the ISMIR community, while also highlighting technical work by women in MIR in different stages of completion. This is the first time we’ve organized such an event, and we’d love to see you there!


An ISMIR Satellite Event

The workshop will take place following the ISMIR2018, featuring a WiMIR reception and the Late-breaking & Demos session. This satellite event aims to complement the conference in three notable ways:

  • Further amplify the scientific efforts of women in the field.
  • Encourage the discussion of proposed or unfinished work.
  • Create additional space for networking.


Opportunities for Research, Networking, and Mentorship

The WiMIR Workshop will combine a variety of activities, including a poster session (see below), networking lunch, and small-group ideation and prototyping sessions under the mentorship of senior members of the WiMIR community. From the poster session to the group activities, the event will emphasize early research ideas that can be shaped and developed through discussions that occur throughout the day!

Who Can Participate?

The WiMIR Workshop is open for everyone to attend, and is free! You do not need to attend ISMIR to attend the WiMIR workshop.

Researchers who self-identify as women are invited to submit short abstracts for poster presentations on projects at any stage of completion, from proposal to previously published work. Preliminary and early results are especially encouraged so that presenters can get feedback from peers and mentors. Any topic broadly related to the field of MIR is welcome and encouraged. Click here to submit a poster. Poster submissions close on August 15, 2018, and acceptance notifications will be sent by August 31, 2018.

Please don’t hesitate to send questions to wimir.workshop@gmail.com.







Opening Remarks



Mentoring Session I (intros and big picture)



Poster Session



Lunch/theme breakout



Mentoring Session II (deep dive into the topic)



Group Presentations



Closing remarks

We look forward to seeing you at the Women in Music Information Retrieval 1st Annual Workshop!

The WiMIR Workshop Organizers

Abstract submission form here: https://goo.gl/forms/hy3ygYnKKS9fTLa13


Mentoring round 2018 is about to start!

After matching nearly 80 mentees and mentors, we are ready to start the mentoring round 2018! We started the mentoring program in 2016 with 40 participants in total; in this third round we welcome more than 150 participants. Thanks everyone for contributing and keeping your commitment! Happy mentoring!

WiMIR mentoring 2018 participants

Mentoring Program Committee

  • Emilia Gómez, Universitat Pompeu Fabra, Spain
  • Ryan Groves, Melodrive, Germany
  • Blair Kaneshiro, Stanford University, US
  • Anja Volk, Utrecht University, the Netherlands

Our mentees reside in Australia, Brazil, Canada, China, France, Germany, Hong Kong, India, Indonesia, Italy, the Netherlands, Norway, Singapore, Switzerland, Spain, Turkey, United Kingdom and USA. They range from high school student to university faculty members and industry employees, and represent a diverse field of interests and backgrounds, such as signal processing, machine learning, computer science, information technology, ethnomusicology, computational musicology, music theory, music composition, music perception and cognition, music performance, music and mathematics, neuroscience, library science, music education, multimedia research, sound design, data analytics.

We thank our generous mentors for dedicating their time to this program:

  • Kat Agres, Institute of High Performance Computing (IHPC), A*STAR, Singapore
  • Steinunn Arnardottir, Native Instruments, Germany
  • Andreas Arzt, Johannes Kepler University Linz, Austria
  • Jeanne Bamberger, UC Berkeley, USA
  • Ana M. Barbancho, Universidad de Málaga, Spain
  • Isabel Barbancho, Universidad de Málaga, Spain
  • Christine Bauer, Johannes Kepler University Linz, Austria
  • Juan Pablo Bello, New York University, USA
  • Brian Bemman, Aalborg University, Denmark
  • Tom Butcher, Microsoft, USA
  • Doga Buse Cavdir, CCRMA, Stanford University, USA
  • Oscar Celma, Pandora, USA
  • Joe Cheri Ross, Indian Institute of Technology Bombay, India
  • Srikanth Cherla, Jukedeck Ltd., UK
  • Elaine Chew, Queen Mary University of London, United Kingdom
  • Tom Collins, Lehigh University, USA
  • Julie Cumming, McGill, Canada
  • Sally Jo Cunningham, Waikato University, New Zealand
  • Matthew Davies, INESC TEC, Portugal
  • Andrew Demetriou, TU-Delft, Netherlands
  • Chris Donahue, University of California, San Diego, USA
  • Georgi Dzhambazov, Voice Magix, Spain
  • Douglas Eck, Google, USA
  • Dan Ellis, Google, USA
  • Mary Farbood, New York University, USA
  • George Fazekas, QMUL, UK
  • Ichiro Fujinaga, McGill University, Canada
  • Nick Gang, Shazam, USA
  • Emilia Gómez, Universitat Pompeu Fabra, Spain
  • Fabien Gouyon, Pandora, USA
  • Ryan Groves, Melodrive Inc., Germany
  • Luciana Hamond, UDESC, Brazil
  • Kate Helsen, The University of Western Ontario, Canada
  • Dorien Herremans, Singapore University of Technology and Design, Singapore
  • Eric Humphrey, Spotify, USA
  • Thor Kell, Spotify, USA
  • Anssi Klapuri, Yousician, Finland
  • Peter Knees, TU Wien, Austria
  • Robin Laney, Open University, UK
  • Audrey Laplante, Université de Montréal, Canada
  • Alexander Lerch, Georgia Institute of Technology, USA
  • David Lewis, University of Oxford, UK
  • Cynthia Liem, Delft University of Technology, The Netherlands
  • Matthias Mauch, Queen Mary University of London, UK
  • Brian McFee, New York University, USA
  • Matt McVicar, Jukedeck, UK
  • Emilio Molina, BMAT, Spain
  • Meinard Mueller, International Audio Laboratories Erlangen, Germany
  • John Neuharth, Microsoft, USA
  • Oriol Nieto, Pandora, USA
  • Dimitri Papageorgiou, Aristotle University of Thessaloniki, Greece
  • Emilia Parada-Cabaleiro, University of Augsburg, Germany
  • Geoffroy Peeters, IRCAM, France
  • Aggelos Pikrakis, University of Piraeus, Greece
  • Elio Quinton, Universal Music Group, UK
  • Preeti Rao, IIT Bombay, India
  • Iris Ren, Utrecht University, the Netherlands
  • Matthias Röder, Karajan Institute, Austria
  • Jimena Royo-Letelier, Deezer, France
  • Spencer Russel, MIT Media Lab, USA
  • Justin Salamon, New York University, USA,
  • Markus Schedl, Johannes Kepler University, Austria
  • Sertan Şentürk, Freelancer, Turkey
  • Kitty Zhengshan Shi, Stanford University, USA
  • Jordan Smith, Ircam, France
  • Mohamed Sordo, Pandora, USA
  • Ajay Srinivasamurthy, Idiap Research Institute, Switzerland
  • Sebastian Stober, University of Potsdam, Germany
  • Bob Sturm, Queen Mary University of London, UK
  • Stefan Sullivan, Smule, USA
  • Mi Tian, Elsevier, UK
  • Derek Tingle, SoundCloud, Germany
  • Douglas Turnbull, Ithaca College, USA
  • George Tzanetakis, University of Victoria, Canada,
  • Rafael Valle, NVIDIA and UC Berkeley, USA
  • Makarand Velankar, MKSSS’S Cummins College of Engineering for Women, Pune, India
  • Gissel Velarde, Consultant at Sony CSL, Germany
  • Anja Volk, Utrecht University, the Netherlands
  • Thomas Walther, Spotify, UK
  • Christof Weiss, International Audio Laboratories Erlangen, Germany
  • Tillman Weyde, City University of London, UK
  • Yi-Hsuan Yang, Academia Sinica, Taiwan
  • Eva Zangerle, University of Innsbruck, Austria

Thank You ISMIR 2017 WiMIR Sponsors!

The recent ISMIR 2017 conference in Suzhou, China continued a recent trend of sponsor contributions specifically for Women in Music Information Retrieval (WiMIR) initiatives during the conference. This year, sponsors funded a guest speaker during the WiMIR plenary session, a WiMIR/Diversity reception in the social program, and substantial travel support for female researchers. These initiatives not only enabled more women to attend the conference, but also provided opportunities for the MIR community to come together as a whole to show support for women in the field, and to learn more about the challenges and benefits of fostering a diverse community.

WiMIR Session @ ISMIR 2017

As part of this year’s WiMIR plenary session, Shawn Carney (Head of Global IT at Spotify) spoke about the importance of diversity in an “increasingly interdependent, interconnected world.” Ms. Carney’s talk, Bye Bye Bias: Promoting Diverse Teams, provided insights into the value of diversity and actionable steps we can all take to work toward it (slides available here). Thank you, Shawn Carney and Spotify, for the talk!


WiMIR/Diversity Reception

For the second year, Amazon Music hosted a WiMIR/Diversity reception during the conference. This year’s reception was open to all conference participants and included full dinner along with a Human Bingo activity to encourage attendees to talk to and learn more about the people around them. Thank you Amazon Music for bringing the community together!


WiMIR Travel Awards

Thanks to contributions from Spotify, Smule, Amazon Music, Gracenote, iZotope, Microsoft, and Steinberg, we were able to offer conference travel support to 22 female attendees of ISMIR 2017 – that’s 40% of the women who attended the conference! Importantly, women of any career stage could apply for travel support, and author eligibility included both accepted full papers (first or supporting author) or a presentation during the late-breaking/demo session on the last day of the conference. In the end, ISMIR 2017 WiMIR travel award recipients ranged from high school students to early faculty, over half of whom were attending the ISMIR conference for the first time.

Some feedback from WiMIR travel award recipients:

I am so glad to be in this community where people care and encourage women in MIR. I am so grateful that you are so supportive. Your support and encouragement, both mentally and financially, mean a lot to many female students like me. I’ll pass on this spirit to help many more people in the future. Thank you.
– Kitty Shi, Stanford University

I am so grateful to have had the opportunity of attending ISMIR for the first time thanks to the WiMIR travel award. Throughout my undergraduate experience, I sought ways to connect my electrical engineering education to my passion for music but had a hard time finding a community that sought to do the same. ISMIR has given me the chance to turn my curiosities into real research. The conference gave me the opportunity to immerse myself in a community of people who are clearly passionate about both music and the technologies that help advance our understanding of it. I am currently applying for PhD programs, and this travel award has helped me confirm that MIR research is the direction in which I want to head.
– Camille Noufi, University of Colorado

Many thanks to our sponsors! Being a junior faculty member, I have been in academia for about 15 years, and this is the only conference, and one of the very few occasions, where I feel female researchers are truly privileged. I especially feel grateful that some female students were able to attend this internationally well-known conference only because of the support of WiMIR travel award. To them, this was their first international conference, first poster, and/or first research presentation. To many of us, ISMIR is the most friendly and inspiring conference, which is certainly related to the diversity of attendees, in terms of disciplines, research topics, place of origins, levels of study/experience, gender, etc. It is essential to keep this merit of ISMIR in the future, so that we can continue attracting and retaining precious talent in MIR. The generous support of sponsorship is highly appreciated, and I believe it will be repaid with a greater future of the field, the community, and the world.  
– Xiao Hu, University of Hong Kong

I truly appreciate that ISMIR can provide this opportunity for me to join this conference. I got tremendous and important insights into my projects through this conference. I also got some very important connections through this energetic community. Thank you!
– Sonia

ISMIR 2017 was the first ISMIR Conference I attended and it was a great opportunity to be able to meet the MIR community empowering underrepresented groups in the field. The WiMIR travel award was one of the major support for me attending the conference. I am grateful to have the support of this encouraging community. I would like to thank the ISMIR 2017 WiMIR travel award sponsors again for their generous and continuous support.
– Doga Cavdir, Stanford University

The WiMIR grant allowed me to attend ISMIR with minimal stress. As an early career researcher, I often have to pay out large sums of money for conferences months in advance and hope to be reimbursed at some point. Having the WiMIR grant not only pay for registration and lodging, but also find my lodging was more helpful and supportive than I can articulate.
– WiMIR travel award recipient

I’m very grateful for your support to make my trip to ISMIR 2017 possible. It is an incredible opportunity for my research career to present my work in the world’s most influential MIR community and receive valuable feedback from researchers all over the world. Also, invigorating talks from the foremost researchers of the field of MIR did inspire me a lot. Thanks again for funding me on this invaluable experience.
– Simin Yang, Queen Mary University of London

Thank you so much for your support for my ISMIR 2017 travel. I have learnt a lot from people in the conference and made progress on my research. This was a great opportunity for me and will be one of the most precious gifts in my life.
– WiMIR travel award recipient

Thank you to the ISMIR 2017 WiMIR travel award sponsors so much for having me, an undergraduate student, joining in the top international conference in MIR. I really enjoyed my time there and was excited to learn about so many inspiring projects and ideas. I look forward to next year’s conference in Paris!
– Shuqi Dai, Peking University

It was because of the generous WiMIR travel award that I was able to attend ISMIR for the first time and present my poster. At this conference, I was able to meet with great professors, researchers, and industry affiliates, as well as have interesting conversations that have encouraged me further in my research endeavors. Hence, I’d like to thank the sponsors for giving me the opportunity.
– So Yeon Park, Stanford University

I am in the last year of my PhD and attending ISMIR was a huge opportunity for networking. Thanks to the WiMIR sponsors and especially Smule for making this happen!
– WiMIR travel award recipient

It was my first ISMIR, and I’m happy to become a member of the society. Thanks to the scholarship I was able to attend the conference and present my ongoing work. It was inspiring by itself, and even more, I received some positive comments and helpful feedback about my research. I’m sincerely grateful to the WiMIR organisers for their efforts to create the program, and, of course, to the sponsors for making it possible.
– Olga Slizovskaia, Universitat Pompeu Fabra

Thank you for so generously providing WiMIR travel awards. As a high school student, I submitted a late-breaking paper to ISMIR with no expectations, so receiving the WiMIR grant was beyond exciting and gave me so much encouragement to keep pursuing my research. ISMIR 2017 in Suzhou, China was incredible. I spoke with researchers from universities around the world and companies like Spotify, Pandora, and Smule; my conversations with people equally passionate about math, computer science, and music allowed me to learn about their projects and gain valuable feedback to expand on my own research. I got a taste of the synergy of working with people from many backgrounds and am discovering how to apply tools from one discipline to another to cross-fertilize ideas. Coming from an all-girls school especially, I am super appreciative of the work WiMIR does to increase opportunities for women in STEM like me.
– Hanna Yip, The Spence School

Thank you for the travel grant, without which it would have not been possible for me to attend ISMIR. Apart from the finances itself, what really stood out was the kinship and the immediate connection that I felt towards other WiMIR grantees. It was great to meet WiMIR researchers from across the globe and get to know them and their research. I also loved the session on Women in MIR. As someone who has worked in the industry for nearly 20 years, I am quite aware of the abysmal number of women in the field and their daily struggles. Many of the suggestions that were brought out resonated with me. Thank you once again for making it happen.
– Vidya Rangasayee, San Jose State University

Looking Forward

We believe that facilitating conference travel, as well as providing an inclusive and welcoming experience at the conference, are critical steps toward building a diverse and vibrant MIR community. We will continue to work with sponsors and other members of the community to welcome women and other individuals from underrepresented backgrounds at future conferences.

Regarding ongoing initiatives, WiMIR-specific sponsorship levels and benefits are now included in the ISMIR 2018 Call for Sponsors. In addition, the WiMIR mentoring program is entering its third round, and mentor/mentee signups are open through November 30. We also welcome feedback from the community at any time on other ways to support women in the field. Email ismir2018-sponsorship@ircam.fr and wimir-mentoring@ismir.net if you are interested in participating as a sponsor of WiMIR at ISMIR 2018, or have ideas for other initiatives!

The ISMIR 2017 WiMIR initiatives would not have been possible without the support of our sponsors, as well as the help and cooperation of the entire ISMIR 2017 Conference Committee, who came together to handle the many organizational and logistical tasks related to the travel grants and conference programming. Thank you also to the WiMIR travel award recipients for participating in the conference, and to those who provided feedback to the sponsors.

Thank You ISMIR 2017 WiMIR Sponsors!

PLATINUM smule-e1497583384943              PLATINUM Spotify_Logo_RGB_Green_WEBSITE

PLATINUM Amazon Music_RGB_Gradient WEB

PLATINUM Gracenote_A_Nielsen_Company_Logo_BLUE (1)   SILVER izotope-logo-black   PLATINUM Microsoft-logo_cmyk_c-gray   GOLD Steinberg_LOGO

Blair Kaneshiro (Sponsorships Co-Chair for the ISMIR 2017 conference) is a Research Scientist in the department of Otolaryngology Head & Neck Surgery at Stanford University School of Medicine. Her current research focuses primarily on objective assessment of auditory function and music cognition using electrophysiological responses. She earned her BA in Music, MA in Music, Science, and Technology, MS in Electrical Engineering, and PhD in Computer-Based Music Theory and Acoustics, all from Stanford. She is active in the Women in Music Information Retrieval (WiMIR) community as co-organizer, with Emilia Gómez and Anja Volk, of the WiMIR mentoring program; as well as with the First-Gen/Low-Income (FLI) community and mentoring program at Stanford. She is an incoming board member of the International Society for Music Information Retrieval.


Sign-ups open for WiMIR mentoring round 2018


For preparing the third round of the Women in Music Information Retrieval (WiMIR) mentoring program, to begin in January 2018,  we kindly invite previous and new mentors and mentees to sign up for the upcoming round through the signup forms linked below in this post.

The WiMIR mentoring program connects women students, postdocs, early-stage researchers, industry employees, and faculty to more senior women and men in MIR who are dedicated to increasing opportunities for women in the field. Mentors will share their experiences and offer guidance to support mentees in achieving and exceeding their goals and aspirations. By connecting individuals of different backgrounds and expertise, this program strengthens networks within the MIR community, both in academia and industry.

Time commitment: four remote meetings between January and end of June 2018.

Who is eligible?

– Female undergraduates, graduate students, postdocs, early-stage researchers, industry employees, and faculty may sign up as mentees.

– Graduate students, industry employees, researchers, and faculty of any gender may sign up as mentors.

– Those meeting criteria for both mentor and mentee roles are welcome to sign up as both.

Faculty: Please share this announcement with female undergraduates in your departments and labs who may be interested in participating. The mentoring program can help attracting newcomers at an early stage to the MIR field.

Sign up to GET a mentor here: http://bit.ly/2AAZIqL

Sign up to BE a mentor here: http://bit.ly/2zuZp3b

Signups close Nov 30, 2017. Mentor/mentee matches will be announced in January 2018.

More information on the program:

For general information check out https://wimir.wordpress.com/mentoring-program/

Report on the mentoring round in 2017, including feedback from participants,  to be found here. Participants’ reports on their experience with the program: Stefanie Acevedo, Magdalena Fuentes, Iris Yuping Ren, Ryan Groves.

Questions? Email wimir-mentoring@ismir.net

We look forward to your response and commitment to continuing the mentoring program!

Emilia Gómez, Blair Kaneshiro, and Anja Volk (WiMIR Mentoring Program Committee)


WiMIR session at ISMIR 2017

We are looking forward to the next WiMIR session at ISMIR conference in Suzhou, kindly organized by our WiMIR co-chairs:

Jin Ha Lee
Jin Ha Lee
University of Washington,
Preeti Rao
Preeti Rao
Indian Institute of Technology Bombay,

Zhongzhe Xiao
Soochow University,
Mainland China

The WiMIR meeting will take place in October 24th from 13:20 to 14:20, according to the program. There will also be a WiMIR reception at 18:00.

For this year’s WiMIR session, we will begin with a brief overview of the group, recognition of WiMIR sponsors, and report on disbursement of WiMIR funding. We will then summarise and discuss various initiatives that happened in the previous year. This will be followed by the talk by Shawn Carney, Director of IT at Spotify, titled Bye Bye Bias: Promoting Diverse Teams. 

Finally, we will wrap up the session with Q&A with Shawn Carney, and discussion of ideas for new initiatives to further support women in the field.  More information is available at the ISMIR 2017 web page.

We thank the generous WiMIR sponsors of ISMIR2017:




WiMIR Mentoring Program Report 2017: the many faces of diversity


Poster design: Julia Wilkins

Blog post by Anja Volk (Utrecht University), Co-Founder of the WiMIR Mentoring Program

We started the mentoring program in 2016, after many years of regular meetings of the Women in MIR group, which is dedicated to promoting the role of, and increasing opportunities for, women in the MIR field. The mentoring program was founded to connect women students, postdocs, early-stage researchers, industry employees, and faculty to more senior women and men in MIR. The program encourages and supports women in pursuing a career in MIR, raises an awareness on issues often faced by women in our field, and establishes networks between different generations, genders, and disciplines within MIR in academia and industry.

In this second round of the program in 2017, the number of participants has more than doubled. We have asked participants for anonymous feedback on their experience with the program after the closing in June 2017, in order to help the Mentoring Program Committee (Emilia Gómez, Blair Kaneshiro, and Anja Volk) to gain insights into what has worked well or less well for participants. With this blog post we share the outcomes of the mentoring round in 2017 as reflected by participants. We hope to provide a general overview on the benefits of this community effort to increase diversity in MIR, and to give an idea of the gains for individual participants.  


Around 50 mentees signed up for the program, residing in North America, Europe, Asia, and Australia. They ranged from high school student to associate professor, coming from a diverse field of interests and backgrounds, such as digital signal processing, computer music, computer science, music theory, computational musicology, music psychology, music performance, music and mathematics, music perception and cognition, computational ethnomusicology, composition, computational neuroscience, digital media, information science and human computer interaction. Mentors came from equally diverse backgrounds and different stages of career, residing in North America, Europe, Asia, and New Zealand, with roughly 1/3 working in industry and 2/3 in academia. Compared to the first round in 2016, we have seen a strong increase in the number of mentors from industry. As in 2016, an equal number of male and female mentors participated.

Matching procedure

We considered a number of different aspects when establishing the matches, such as general research interest and background, language, time zone, level of seniority, and specific requests from mentees on certain research or career topics. While it was often impossible to find a perfect match on all points, we strived to find the best possible overlap in commonalities. Participants were in general happy with their matches according to the feedback (on a scale between 0 and 5, 87% mentees rated the fitness of their match with a 4 or 5, so did 67% of the mentors). We do feel ready for the next MIREX challenge for helping us to solve this big puzzle: what would be the best algorithm for automatically matching the participants? One big challenge was the difference in time zones, as it is not always possible to find mentor and mentee within the same time zone, or even same continent.  Participants commented that both the commonalities in the matches were helpful, but also the differences for gaining new perspectives, such as discovering how research is organized in different countries.

Mentoring sessions

Participants had signed up for maximal 4 remote meetings in total between January and June 2017, while 42 % of mentees reported 4 and more meetings, others reported fewer meetings.

The following topics have been discussed in the mentoring sessions according to the feedback, with decreasing order of importance:

  • Career paths in academia
  • Career paths in industry
  • Work/life balance
  • Graduate school
  • Dealing with sexism
  • Balancing career with family/children

What did mentees gain

Overall, the mentees were very positive about the mentoring sessions – check out the gratitude wall – and have fun! Mentees reported very different aspects as important gains, from getting a general overview on research in music and technology, to getting a clearer picture on different career options, but also in receiving very concrete help in writing a paper or grant proposal. Here we report some examples on what they have taken home from the program:

  • Cooperation on a conference article
  • Feedback on research
  • Sharing questions and concerns
  • Getting a bigger perspective
  • Better understanding of priority of funders
  • Useful advice about internship
  • Gain a different perspective than those of my immediate colleagues
  • Getting to know a very wide field of research in music and technology fields
  • Better confidence in my abilities and professional options
  • Better understanding of different career paths in industry and academia

Examples of what mentees say about the program:

I saw possibilities and perspectives of people who ‘know better’ about that world in which I’m moving towards to but not quite there.

The gender disproportionality somehow to me brings fear of not choosing a secure career option. The mentorship program has been a confidence booster to me.

The WiMIR mentoring program clearly helps to create a better network among the members of the field, because it introduces people that otherwise would probably have never met.

For more detailed descriptions of benefits for mentees, please check out the blog posts by Stefanie Acevedo, Magdalena Fuentes and Iris Yuping Ren.

What did mentors gain

Many of the mentors indicated that they have taken valuable insights from the conversations, here are some examples:

  • Evaluating their own career path and reflecting on their own priorities
  • Gaining perspectives on struggles and concerns of junior staff in industry
  • Learning about differences in academic systems between North America and Europe
  • Mentees brought new ideas, mentors learnt something new about themselves
  • Good experience that their background and skills are useful for someone else
  • Being inspired by young researchers in the field
  • Gaining a friend

Examples of what mentors say about the program:

There are few things during my academic work day that take less time and have such immediate and longer-term impacts.

It was exciting to me to see my mentee being eager to proudly tell me about new accomplishments and insights and me being proud on these accomplishments as well. I got the feeling that I may have had a positive impact on the mentee and that both sides actually likewise benefited from the mentoring program.

I got to know brilliant people whom I wouldn’t have a chance to know otherwise.

For more: check out the gratitude wall from the mentors, and Ryan Groves’ blog post on the perspective of a mentor!

General feedback on the program

Both mentors and mentees reported a positive overall experience of the mentoring program: 88% of mentees gave it a 4 or 5 (on a scale between 0 and 5); 73% of mentors gave it a 4 or 5. The majority considered the time span between January and June appropriate, though 46% of the mentees and 32% of the mentors would have preferred a longer time span. Some participants reported difficulties in scheduling meetings, sometimes due to time zone differences.

Importance of the program for increasing diversity in MIR

Participants considered the extra support and push for women in our gender-imbalanced area as an important point of the program for increasing diversity, along with the factor of helping to make women in the field more visible, as well as attracting people from other fields who might learn more about MIR through this program. Participants also commented on the potential of the program to provide (male) mentors with a better understanding on how to make their institutions and themselves more accessible and inclusive.

New ideas by participants :

Participants mentioned a number of new ideas in the feedback form, such as

  • Make peer mentoring accessible for mutual support of mentors, such as on discussing papers or proposals
  • Connect mentees with each other through mailing list or chat platforms for exchanging ideas with others in a similar situation
  • Create profiles of women who have participated in the program on website for visibility
  • Get together at conferences, organize local networking
  • Establish contacts to high schools for early information on MIR

Conclusions by mentoring program committee for next round

We are in the process of discussing how to implement the new ideas mentioned by participants. Here are some ideas:

  • Mentors can indicate in sign up form whether they are interested in peer mentoring and what they would be interested in discussing with a peer. We will establish email contact between all mentors who are interested in peer mentoring, including information what they want to discuss, and then mentors can contact each other. Mentors can also indicate whether they would be interested in participating in a forum with other mentors.
  • Mentees can indicate in signup form whether they want to be part of email group or group chat with other mentees on exchanging ideas with peers. We establish the contact between all mentees who are interested, and then leave the mentee group to organize themselves.
  • We need volunteers for creating profiles of women for the website.
  • For anyone being in contact with high schools in their local area, we can provide a Power Point presentation about the mentoring program.
  • If anyone would like to organize a local networking event, please let us know for helping to spread the word about it. 

Note: If anybody has a comment or different suggestion, and wants to get involved in organizing, please contact us at wimir-mentoring@ismir.net.

A note from the program committee

We would like to thank all participants for making this round of the mentoring program happen! The doubts and concerns that are often mentioned by mentees when they sign up for this program — on whether or not there might be a career for them in this field — have been openly discussed in the mentoring sessions. We are happy that this community pays an invaluable contribution of encouragement to meet these concerns. Moreover, participants help to introduce MIR with its different disciplinary facets to people who have sometimes hardly heard about this field before, or to those with a different disciplinary background. Both mentees and mentors appreciated a new perspective on a different discipline, generation, gender, career path, country or continent – as a testament to the fact that “Mentoring is a two-way street” (Steve Washington) which considers many different facets of diversity. Or, as Amy V Beeston has put it in her blog post, we find courage through encouraging others, such that mentoring is a mutual gain. And in our case, we extend the gain to the third dimension of the mentoring program committee: by organizing this program, we provide a frame to be filled in by the participants, as it is up to the mentors and mentees to conceptualize whatever support is helpful in their individual sessions. Learning about the diverse outcomes, new emerging connections and ideas resulting from these individual cases means for us to see our efforts creatively multiplied into all kinds of directions – a moment of great joy, which we would like to share with all participants.

Anja Volk (Utrecht University), holds master degrees in both mathematics and musicology, and a PhD in the field of computational musicology. The results of her research have substantially contributed to areas such as music information retrieval, computational musicology, digital cultural heritage, music cognition, and mathematical music theory.  In 2010 she has been invited to join AcademiaNet: The Portal to Excellent Women Academics. She is founding board member of the International Society for Mathematics and Computation in Music (SMCM).  Between 2013 and 2015 she served as a board member of the International Society for Music Information Retrieval. In 2016 she launched together with Amélie Anglade, Emilia Gómez and Blair Kaneshiro the Women in MIR (WIMIR) Mentoring Program.  She co-organized the launch of the Transactions of the International Society for Music Information Retrieval, the open access journal of the ISMIR society, and is serving as Co-Editor-in-Chief for the journal’s first term.


WiMIR Mentoring 2017 Gratitude Wall


Poster design: Julia Wilkins

This blog post displays notions of mutual gratitude from participants of the WiMIR Mentoring Program in 2017. The program run between January and June 2017, with four remote sessions between mentee and mentor. Participants from North America, Europe, Asia, Australia and New Zealand came from a wide range of disciplinary background in music and technology. With this gratitude wall we share some of the benefits participants have experienced. Thanks everyone who has contributed to this wall! Have fun reading!

Mentees’ gratitude towards mentors

Thank you for your time, enthusiasm, and intelligence in accompanying me in this important transition from student to independent researcher! Your words about the method of work, interdisciplinary connections, and trust for the job search are very important and I am so grateful to you for these. Thank you so much!

Hi A. I see this opportunity to thank you publicly. You have been a great mentor and I will always be thankful to you for your help in making such a huge transition. All those DSP sessions have now enhanced my confidence and I hope to contribute to the MIR domain in the near future. Of course, I am going to continue to have sessions. Thank you once again ! 🙂

I am grateful for my mentor to take time out of his schedule to connect with me.

Thank you very much for taking your time, and for sharing your resources generously!

Thank you so much for your time, patience, answering all my questions and sharing your experience with me. It was a great program and it helped me get a more complete picture of the life after the PhD.

Thanks so much for the sessions! It’s always been a pleasure to talk to you. Very important to have someone’s opinions from the outside world. I learned a lot!

I feel very grateful for being part of the WiMIR program and to have an awesome mentor. It passes on skills, shares experience, and simply doubles the joy during research.

Thank you very much for your time and effort. You helped me in being more secure and better understanding what I was moving towards to. It’s funny how it may seem a simple conversation, but actually has a great effect.

Thank you for generously sharing your time and experience, and for giving me the opportunity to air uncertain thoughts in a low-pressure environment.

Thank you so much for all the advice that you gave me about both my academia and industry path. I truly valued your input as I was choosing a summer internship, and I would not feel confident in my choice without your help. Your openness and willingness to help and discuss anything was much appreciated, and I also loved hearing about your experience at your job and past institutions. I look up to you in many ways an aspire to follow a similar path to yours. You inspire me to want to be a great mentor to another young woman someday! Thanks for everything!

Grateful for the support and the motivation!

Thank you for your great understanding regarding all the doubts and concerns I had (and still have) in relation to a career path and life. Our conversations have been a great comfort and I am very grateful for your advice.

Thanks for being open and helpful from the very beginning!

My mentor was kind, encouraging, and easy to talk to. I could not have asked for a better mentor!

Hi, very glad to know and talk with H. Though I could not go through all the tracks and had short term to discuss our subject, it was impressive enough.

Thank you so much for your encouragement and insight into ways to get more immersed in the field of MIR. You showed me how it’s done.

It was great to talk to him! He’s an outstanding researcher and above all he was very humble and nice in all the meetings. I would like to thank him very much for his patience and time!

Thank you for taking the time to engage me like a colleague, sharing your knowledge and giving support. Your aid was indispensable.

Thank you so much! Having an open mind and willingness to help people is so important and you have truly left an impact. I know now that I will always have someone I can look to for guidance and support and it really means a lot.

Thank you to all who organized this program! It was truly a great experience and allowed me to talk to someone working in the field first-hand.

Thank you to my mentor for helping me explore different career paths within the MIR field.

Mentors’ gratitude towards mentees

Dear mentee, thank you for being my mentee for the last six months. During the course of the mentoring program, we got to know each other bit by bit and found that we do have a lot in common. This made it really easy to talk and to me, our telephone conferences simply flew by. I watched you taking a number of important steps and hope that you continue your path. I hope that you did enjoy it as much as I did and that you could actually gain from the program as much as I did.

Thanks for participating! Keep the good work up 🙂

Thank you for sharing how your love of music performance informs your research!

Thank you for being such an enjoyable companion. I was surprised by how much I looked forward to our discussions, and how quickly they went by.

I am glad that you worked hard to complete an ISMIR manuscript even though it was not ready. Sometime you just need to press on.

Thanks for all of our conversations!

Thank you for different view points and the research directions in Indian classical music.

It was a pleasure talking to a young and motivated student following an academic path.

Thank you for your curiosity and interest!

I’m so glad this initiative exists. Thanks a ton, organizers!

Thank you for your commitment to MIR despite the lack of encouragement from several quarters!

Keep on rockin’ mentee! Keep connected to MIR, and enrich MIR with these new tools you are learning in a neighboring field.

Thank you for your trust and patience while I learn the ropes of being a more effective mentor!

Follow your dreams!

Thank you for the nice chat on the thrilling steps of learning playing music instruments and enjoying music in general. I hope I will see you some day fulfilling your musical dreams!

Thanks so much for the honest, open and good-hearted sharing of experiences, ideas, questions and the occasional doubt. I saw myself reflected on your hopes and concerns more than expected, and I believe the experience not only to improve as a mentor, but as a member of the MIR community too. Thanks!

Thank you for the opportunity to discuss your research and your aspiration on pursuing scientific inquires!

I look forward to mentoring future MIR researchers!


Round 2 of WiMIR travel awards to attend ISMIR 2017 in Suzhou, China

Round 2 of travel awards to attend in Suzhou, China, Oct 23-27 is now open.

We have made a slight adjustment to the timeline for late-breaking demo (LBD) submissions associated with Round 2 of the WiMIR travel awards for the ISMIR2017 conference. Current information is below.
Application form: http://bit.ly/2i5nCpc
Deadline to apply: August 31, 2017
Acceptance notifications: September 8, 2017
Deadline to submit completed LBD draft (for LBD recipients): October 8, 2017
Deadline to complete minor LBD revisions and submit final version (for LBD recipients): October 22, 2017
Eligibility requirements:
– Female author (first or supporting) on accepted full paper; and/or female first author on accepted late-breaking demo (LBD) submission.
– WiMIR applicants do not need to be students.
Questions? Email ismir2017-grants@ismir.net

Convolutional Methods for Music Analysis

Blogpost by Gissel Velarde, researcher in Music Information Retrieval and WiMIR mentor, summarising her PhD work.  

In April this year, I defended my thesis entitled: Convolutional Methods for Music Analysis, available here.

This work introduces convolution, its relevance for perceptual tasks, and its effect on music analysis in applications to music segmentation, pattern discovery and classification. The methodology we have followed was to systematically study and evaluate the effect of convolution (filtering) and other processing techniques together with machine learning algorithms, from k-nearest neighbours, single linkage, support vector machines to convolutional neural networks.

The novel convolution-based methods for music analysis presented in my thesis have been developed together with my supervisors Associate Professor David Meredith, Aalborg University and Senior Lecturer Tillman Weyde City, University of London, as well as in collaboration with researchers from The Austrian Research Institute for Artificial Intelligence: Carlos Cancino Chacón and Maarten Grachten.


Picture of PhD Defense of Gissel Velarde, April 2017, Aalborg University

Gissel Velarde completed her PhD studies in computer science at Aalborg University, supported by a scholarship from the Department of Architecture Design and Media Technology, Aalborg University, and partially supported by the European Commission, FET grant number 610859. She also holds a Masters degree in Electronic Systems and Engineering Management from the Südwestfallen University of Applied Sciences, supported by a DAAD scholarship. Her Licenciatura degree in Systems Engineering was obtained from the Universidad Católica Boliviana. She was a research member of the European Commission Project “Learning to Create” (Lrn2Cre8).

Before dedicating to technology, Velarde studied piano at the Conservatorio Plurinacional de Música in La Paz, Bolivia and won as a pianist, several prices and honors.

During her doctoral studies at Aalborg University, she published research papers on computational methods for music analysis. She was teaching assistant on the Master of Science program in Sound and Music Computing and supervised various projects of the Bachelor program in Medialogy.


Approaching Feminism as a Male Data Scientist

Blog post by WiMIR mentor Ryan Groves, co-founder of Melodrive


Painting Equality used with permission from artist Osnat Tzadok, find original here.

The internet has provided a new platform for an obscene amount of information. Anyone with a computer and a connection can now be heard in the international community. Through the accessibility of information, citizens have become journalists, comedians, celebrities, laughing stocks, community leaders and even scientists just through the means of access to this information tsunami. One particular aspect of this is the ability for marginalized groups to directly confront those who are more privileged, or even perpetrate that marginalization.

I am a man. I had a relatively privileged upbringing–good schools and active parents. When I first started reading about feminism, I had the knee-jerk reaction that most men have: “They couldn’t be talking about me”. Surely I was a more-informed member of the opposite sex. Surely all of my accomplishments were based on my merit, and not on some advantage bestowed unto me. Surely I wasn’t gaining those advantages through the disadvantages of my peers.

As a data scientist, I teach machines how to understand human problems, and to perform human-like solutions. I decided to do what a good data scientist would do–to gather evidence, form a hypothesis, train the model to solve that problem, and test. Only this time, I’d be the subject.

Gathering Evidence

Let’s talk about the elephant in the room: Mansplaining. According to the New Republic [1], the essay that kicked off the whole idea was by the decorated author, Rebecca Solnit, in her piece, “Men Explain Things to Me; Facts Didn’t Get in Their Way”. In it, she says that “the out-and-out confrontational confidence of the totally ignorant is, in my experience, gendered. Men explain things to me, and other women, whether or not they know what they’re talking about. Some men”. Even in my marginally-more-enlightened state, after having opened myself up to this issue, I still find my instinctual male reaction kicking in when I read this sentence, which is to reject this notion outright. But that is exactly the point–why would I not approach this as evidence, as opposed to rejecting it as opinion? The author continues:

Every woman knows what I’m talking about. It’s the presumption that makes it hard, at times, for any woman in any field; that keeps women from speaking up and from being heard when they dare; that crushes young women into silence by indicating, the way harassment on the street does, that this is not their world. It trains us in self-doubt and self-limitation just as it exercises men’s unsupported overconfidence.

As a man, this was initially a foreign idea to me–an issue of which I was totally unaware.

The problem goes beyond Mansplaining. More recently, I read a really insightful blog post by a female engineer & designer, Nikki Lee, titled “Ride Like a Girl”. In it, she relates the experience of living as a woman in a world designed for men to being a biker in a world designed for cars. In it, she says:

Maybe you’ve noticed that cars are kind of scary. They are more or less scary depending on where you live — if you’re on a nice calm street in Seattle, drivers will give you plenty of room and wait patiently for you. Other places, drivers will try to run you off the road. And no matter where you are, you know that the cars around you could really mess you up if something went wrong.


In places with great cycling infrastructure, it’s really easy to get around just as efficiently as driving. But most cities don’t have that. These environments aren’t just not built for you, they’re constructed in a way that actively excludes you.

This analogy really resonated with me, because, like most people, I’ve had this experience while biking. I have indeed witnessed negligent drivers who impose the risk of real physical harm on bikers through their negligence. I have been held to a double-standard by having those same negligent drivers call me out for minor traffic infractions.

In industry, there are plenty of examples of the same disadvantages. I recently attended a Meetup event for gaming and game development in Berlin, and had the honor to hear a talk given by Brie Code. Brie Code is a speaker, writer, and the CEO of a new game studio, Tru Luv Media. She has worked for years in the games industry as a game AI developer and designer. Brie had always found that she had a very different response to games than traditional gamers. As she presents in her blog post on the topic:

[M]ultitudes of white masculine gamers who dominate the games industry have made experiences that are relevant to them but not to most people.

Brie often didn’t feel the “fight-or-flight” response to dangerous in-game situations. When she tried to explain this to other game developers and executives, they would confront her about it, even indicating that her own experience was wrong. Brie decided to do some research into the underlying assumptions that fuel those opinions. The research she discovered was compelling.

The most-commonly-known physiological response to threatening situations in games is fight-or-flight. As Brie Code puts it:

With fight-or-flight, your sympathetic nervous system kicks in and releases adrenaline followed by dopamine. If you like games like this, it’s probably because adrenaline and dopamine are very enjoyable. Your pupils dilate. Your heart beats faster. Your airways open up. And you feel exhilarated. You feel alive. You feel powerful.

Because Brie (as well as many of her friends) did not respond to games in this way, she dug up the psychological research around these responses, and found a completely different, competing response: tend-and-befriend. As Brie describes:

If you experience tend-and-befriend, it’s because your body releases oxytocin or vasopressin when you’re stressed, followed by opioids. This calms your sympathetic nervous system so you don’t get the flood of adrenaline. Instead of wanting to fight or to flee, you stay relatively calm, but aware. Your pupils dilate, you become fearless, and you are less sensitive to pain. You instinctively want to protect your loved ones, to seek out your allies, and to form new alliances. Oxytocin intensifies social feelings, and opioids feel extremely warm and lovely.

Research shows that oxytocin is involved in the physiological response to these threatening situations more-so for women than for men. In order to discover why this tend-and-befriend response was so overlooked, Brie did even more research. Prior to 1995, only 17% of the participants of psychological stress studies were female. In addition, according to an article by Think Progress, a 2014 review of sports and exercise studies showed that only 39% of 6 million participants were women. Brie found that this bias existed in things such as air-bag deployment, or identifying the signs of heart attacks.

However, it’s not only women that respond to games with tend-and-befriend. It seems that there is simply more to the picture than the traditional fight-or-flight response, which is exactly what Brie set out to prove.

Even in the highest office of the (American) land, female staffers were feeling overrun by their male counterparts. So much so, that they devised a strategy of mutual affirmation.

If we’re forming our opinions based on biased information, and excluding opposing opinions, then even what we consider to be fact is potentially false. It certainly seemed there was a common theme in all of these examples, which was succinctly described in the previously-mentioned article by Nikki Lee: These environments aren’t just not built for you, they’re constructed in a way that actively excludes you.

Forming a Hypothesis

I decided to challenge myself. Perhaps, rather than hypothesizing that all of this evidence was untrue, and trying to prove that, I should do exactly the opposite: I chose to hypothesize that all of this was true, and challenged myself to prove that it was.

Training myself to be aware

Since making this decision I’ve tried to be more aware of the issues facing women specifically. But how does one really change her own perspective? It isn’t solvable with a single bout of effort. It needs to be as consistent of an effort as it is for those who are not at a natural advantage in society’s constructed environments–one needs to be as aware as a biker in a city. As has been evident with the recent political happenings in the USA, sources of information can have a huge effect on your thoughts, habits, and perspectives. The two camps for Clinton and Trump were both guilty of consuming information that supported their own perspectives, which was why it was such a rude awakening for the Clinton supporters when Trump was elected. In general, we think of receiving information as a passive process, and in many cases it is hard to avoid consuming certain information. However, there are ways to customize your acquisition of information, and to control the perspectives that you choose to expose yourself to. In effect, you can run your own self-inflicted propaganda campaign.

I also endeavored to prove the hypothesis by gathering my own data. I found there to be ample evidence of the gender-based slights in my daily life. A female coworker filed a sexual harassment complaint, and the whole company was subjected to a sexual harassment seminar–with the glaring exclusion of the offender. Another female colleague was asked her opinion on her area of expertise, only to have them initially reject her opinion outright, and then claim her idea as their own in the final version. In a pickup basketball game, a female teammate suggests reducing the game to 4 on 4, because we only have teams of 5 and 6, and it would be hard for her team (of 5) to be running for the entire game with no substitutes. A man responds, insisting it be 5 on 5, and shouts “we’re men, and we want to run!”.

I’ve even noticed simple micro-aggressions in the academic world. At a recent conference, I walked up to a particular poster presentation in the middle of a conversation between the presenter and a female participant. Immediately, the presenter’s focus shifted from the woman to me, and it was as if the woman was no longer part of the conversation.


With the mounting evidence from both personal experience and outside sources, it seems that gender issues are real, and pose a serious barrier to equal opportunity. So how do I use this gained perspective to make a real change?

Spread the Word

One constructive approach is to evangelize my own personal process, and to encourage other men to change their perspective. It is indeed both genders’ responsibility that people are treated fairly. This blog post is my first attempt at that. But it also involves ongoing discussions and dialogue.


Now that I am convinced of my hypothesis, it’s my responsibility to confront micro-aggressions and unfair treatment that occur in my surroundings.

Continue My Personal Awareness Campaign

My perspective is not perfect, and I don’t expect it ever to be. For the last 2 years, I’ve been a mentor for the Women in MIR (WiMIR) mentoring program. It’s a fantastic initiative that is trying to address some of these gender-based discrepancies in academia, with a specific focus on the MIR (Music Information Retrieval) community. Part of the reason that I like to be a WiMIR mentor is to simply be aware of the issues that women face in the workplace from their perspective, since there are always things that I personally overlook coming from the perspective of the opposite gender.

Build a Positive Work Environment

As a business owner in my capacity of co-founder of Melodrive, I have the unique opportunity to sculpt my own business’ work environment, and it’s my responsibility to create an environment that is as inclusive as possible. Recently, the Augmented Reality company Magic Leap had a lawsuit alleging gender-based discrimination. In the lawsuit, there contains a really thoughtful list of recommendations for a company that wants to be more inclusive (written by Tannen Campbell).

  • Creating “parents’ guides” for cities where Magic Leap had offices, and listing recommended doctors, babysitters, etc. for newcomers
  • Establishing internships for female students to code/build for mixed reality
  • Creating an internal mentorship program pairing men with women;
  • Increasing paternity leave to show that Magic Leap values a man’s role in child caregiving and allows busy moms to return to work sooner if they choose;
  • Tying diversity to extra bonuses, e.g., giving a department head an additional bonus for increasing gender diversity
  • Implementing mandatory “unconscious bias training” for leadership;
  • Demonstrating a commitment to encouraging young girls’ interest in tech education by replacing the “swag”–T-shirts, notebooks and the like–handed out to important visitors with a donation in the important visitor’s name to Girls Who Code, and organization devoted to overcoming the gender gap in tech jobs.
  • Creating and appending an “Equal Pay Guarantee” stamp or seal on all Magic Leap’s position descriptions in recruiting material and elsewhere, evidencing Magic Leap’s commitment to equal pay for equal work within the same tier
  • “Fishing where the fish are” by recruiting employees from a list of colleges, provided by Campbell, with the highest number of women in STEM (Science, Technology, Engineering and Mathematics) departments

With all of these new data points, and my somewhat-improved perspective, it will hopefully be easier to be proactive to create a non-hostile work environment and accommodating employee policies as a small business owner. Additionally, perhaps I’ll be able to move the needle to a society that is more open and inclusive. And while I feel that I have personally made progress in being more in tune with the perspectives of others, I don’t feel that I’ve completed my task. This is an ongoing challenge, just like it is for those who experience disadvantages in their daily lives and beyond.

  1. https://newrepublic.com/article/118555/rebecca-solnits-men-explain-things-me-scourge-mansplaining

Ryan Groves is a computational music theorist, composer and data scientist. He received his B.S. in Computer Science from UCLA, and continued on to complete a Master’s in Music Technology from McGill University. As the former Director of R&D for Zya, he developed a musical messenger app that automatically sings your texts, called Ditty. Ditty won the Best Music App of 2015 from the Appy Awards. In 2016, his research in computational music theory was awarded the Best Paper at the prominent music technology conference, ISMIR. With his new venture, Melodrive, he and his co-founding team of two PhDs in Music and AI are looking to build the world’s best artificially intelligent composer, and to change the way music is experienced in video games and virtual environments.


Mentorship as a way to mind the gap in music academia and to prepare students for the “real world.”

Blog post by WiMIR mentee Stefanie Acevedo, PhD Candidate at Yale University

I knew I wanted a career in music academia since I was fifteen. Now, as I begin the last year of my PhD program in music theory, I feel a mixture of fear, eagerness, and sometimes, uncertainty as to whether I wish to continue in the field. This comes not only due to increasing hostility toward the “liberal conspiracy” of higher education, budget cuts across the board for humanities and music programs, and increasing corporatization of Universities, but also due to slowed (and perhaps even declining) progress for women’s and minority rights in the United States. After spending so many years in graduate school, I worry that all of that effort will be for naught and that my student debt will only grow deeper and deeper due to accruing interest while I make ends meet as an adjunct or visiting professor.

Then again, that anxiety may just be coming from my impostor syndrome [1].

Yet the reality brought on by many of these problems ring true, especially for individuals who make up minorities in musicology fields (women, people-of-color, people with disabilities, and LGBTQ individuals alike): not only must we navigate the world as minorities, but we are also facing a volatile job market.

As a rising educator, then, how can I speak to my students, especially those who are minorities, and tell them that music is a worthwhile career? How can I responsibly educate my students and let them know that, despite spending many years and dollars putting themselves through graduate school, they might have to face years of uncertainty on the job market?

This is where mentoring programs by organizations like WiMIR play a large role.

But first, let us ignore the current job market and focus on the benefits of mentoring. We know that mentoring and support systems allow minority students to thrive [2]. Many minority students are surrounded by societal pressures and, consequently, insecurity – a mentor, aware of the psychological and social dynamics at play, is then able to aid the student in reaching their goals. I, personally, have been lucky to have a PhD advisor who is sensitive to the hardships faced by minority students, and can thus, guide me in matters other than my dissertation research. I am also very lucky to have a wide support network of past professors and mentors who have encouraged me along the way. Many students, especially minorities, do not have that type of support from their advisors or professors, and could benefit from these type of relationships beyond their immediate school environments.

Further, research has shown that women and other minority faculty are more likely to take on mentoring roles than non-minority faculty [3]. This can be problematic in, at least, two ways: A) The amount of time spent on mentoring and related service can compromise minority faculty’s research time (affecting advancement in their field) [4] and B) in departments were minority faculty are scarce, students may not be able to receive the full support they require (leading to lower diversity). Organizational mentoring programs, such as WiMIR’s, can definitely provide outside help to attenuate these problems. These programs also have the potential to indirectly alter department cultures. By becoming mentors, non-minority faculty members can learn and adapt their mentoring to better suit the needs of minority students (and faculty) – they are often even more willing to mentor in the future [5]. Many benefits arise. First of all, minority faculty would be less burdened, giving them more time to research or extend their service elsewhere. If a wider range of faculty invested time into and valued mentoring and similar service more, those activities may be better appreciated by the University as a whole – the service may then be weighed more heavily on, for example, the tenure dossier [6]. And, finally, as non-minority faculty become better attuned to issues faced by minorities, they can facilitate change in department cultures toward inclusivity and diversity [7].

More importantly, though, mentoring programs by organizations such as WiMIR can aid students in diversifying their interests in order to better prepare them for successful careers. As an educator in music, I believe it is my duty to enable students to follow their dreams, but also to prepare them for the real world. As a Hispanic woman, I want to increase the diversity in music theory, but I feel a responsibility to my students to give them the broader picture: academia is cutthroat, the road is long, and job prospects are difficult. I want students to be able to follow their hearts and passion for the arts, but I also want them to have financially-stable and bright futures. The best possible way to prepare a student for a music career, in my opinion, is to diversify their portfolio with a secondary interest in order to develop lucrative skills (not just for a job at a music department, but also for a job in Arts Management at BMI or ASCAP, or as a Data Scientist at Spotify or Google). In my case, I diversified by pursuing a master’s degree in experimental psychology and learning computational skills. We need to be marketable as specialists in music that can apply that knowledge outside of the concert hall or theory classroom. While Universities tout interdisciplinarity, resources are often lacking and students may not have the knowledge, time, or guidance to seek out secondary interests (especially at disadvantaged schools). Not many students can afford the luxury of getting multiple degrees. At many schools, a music degree does not provide training beyond the traditional Western Classical music curriculum. This, then, is where external mentorship can aid students to not only experiment and define other interests, but also gain exposure to and prepare themselves for alternate career paths that also utilize their musical talent. Even for older students, like myself, or those who have already graduated, cross-disciplinary mentorship can help us expand our horizons, leading to a broader portfolio, an increased awareness of the applications of our research, or even, a back up career plan.

Stefanie Acevedo is a PhD Candidate in music theory at Yale University. She is a past member of the Society for Music Theory’s Committee for the Status of Women, a past board member of the International Alliance for Women in Music, and currently serves as a member of the Graduate and Professional Student Title IX Advisory Board at Yale. Her dissertation is a computational and EEG study of popular harmony expectation. She is currently a mentee in WiMIR’s mentorship program.


  1. Peteet, B.J., L. Montgomery, and J.C. Weekes (2015). “Predictors of imposter phenomenon among talented ethnic minority undergraduate students.” The Journal of Negro Education 84(2), pp. 175-186;  Richards, C. (2015). “Learning to deal with the Impostor Syndrome.” The New York Times, October 26.
  2. Thomas, K.M., L.A. Willis, and J. Davis (2007). “Mentoring minority graduate students: issues and strategies for institutions, faculty, and students.” Equal Opportunities International 26(3): pp.178-192, doi: 10.1108/02610150710735471; Blackwell, J.E. (1989). “Mentoring: An action strategy for increasing minority faculty.” Academe 75(5), pp. 8-14.
  3. Acker, S. and G. Feuerverger (1996). “Doing good and feeling bad: The work of women university teachers.” Cambridge Journal of Education 26(3), pp. 401-422.; Flaherty, C. (2015). “Negotiating Balance.” Inside Higher Education, April 22.
  4. Guarino, C.M., and M.H. Borden (2017). “Faculty service loads and gender: Are women taking care of the academic family?” Research in Higher Education.
  5. Ragins, B.R. and J.L. Cotton (1993). “Gender and willingness to mentor in organizations.” Journal of Management 19(1), pp. 97-111.
  6.  Aguirre, A., Jr. (2000). “Women and minority Faculty in the Academic Workplace: Recruitment, Retention, and Academic Culture.” ASHE-ERIC HIgher Education Report 27(6).
  7. Baez, B. (2000). “Race-related service and faculty of color: Conceptualizing critical agency in academe.” Higher Education 39(3), pp. 363-391.

Transitioning from Master’s to PhD: changing the scene from Uruguay to Paris

Blog post by WiMIR-mentee Magdalena Fuentes

Based on my experience, I think that the WiMIR mentoring program can make a difference in how young women join the MIR community. I was first introduced to the mentoring program by Martín Rocamora (Universidad de la República), my Master’s advisor in Uruguay, the country in South America where I come from. In my country, there aren’t many people working in MIR, and when I first joined the mentoring program I wasn’t involved in the community yet. I found the idea of being in touch with experienced people from the MIR community who could talk to me about different scenarios very motivating.

During the same period that I had meetings with my mentor Ana Maria Barbancho (Universidad de Málaga, Spain), I did an internship on a MIR-related task in Paris. At that time, I was trying to decide what to do after, and all the exchanges with the people at the lab in Paris and my mentor were very enriching. The different points of view were valuable for getting an idea of what the MIR community was like and what I really wanted to do. Being in contact with my mentor was helpful because I could discuss things from another point of view, complementing the other opinions people offered. After my internship, I enrolled in a PhD program in France, and I’m currently working in MIR at the labs L2S (CentraleSupélec) and LTCI (Télécom ParisTech).

The MIR mentoring program itself offers a wide and interesting context for discussion. The topics that were proposed for the meetings (life/work balance, academic career, etc) are issues that are relevant to our daily life but in my experience they are not commonly discussed as they should. So it was very nice to have the opportunity to talk about these topics with an experienced person who also has similar interests to mine. Furthermore, there is also room for technical discussions and exchanges, which is a great help for someone who is starting in the field and is generally full of doubts. I’m currently taking part in the second round of the program with a different mentor, Justin Salamon (New York University), and once again it has been a very enriching exchange for which I’m very grateful.

Initiatives like the WiMIR mentoring program encourage diversity in the MIR community and stimulate young researchers to get more involved in the field. I think it’s worth starting more enterprises like this, in particular those encouraging the participation of both male and female young researchers from places where the MIR community is not yet strongly present.


“Finding courage in encouragement” by Amy V Beeston (WiMIR mentee)

Post by Amy V Beeston, one of the mentees of our mentoring program:

I am happy to have been invited by Women in MIR to blog about a recent paper, co-authored with Lucy Cheesman and Liz Dobson, which I presented at the last Digital Music Research Network (DMRN) meeting in London. Our paper reported on a community-building project underway in the north of England, which aims to support and encourage women and girls in (and into) academic and industrial careers relating to music technology.

We were recently awarded a Catalyst: Festival of Creativity grant as part of a city-wide Year of Making celebration in Sheffield. This allowed us to run a series of 8 expert-led workshops, peer-learning maker-space days and a monthly social gathering. These provided ongoing opportunities for women and girls who may have felt excluded or uncomfortable in male-dominated environments to meet, share knowledge formally and informally, and thereby develop their technical and creative skills. Averaging 10 registrations per workshop, our sessions covered a wide range of topics: sound synthesis, machine listening, performance hardware, electronic prototyping, live coding, data sonification, looping and DJing. Despite being labelled as beginners’ workshops, over two-thirds of participants reported some pre-existing familiarity with the topic through their work or studies. Though participants’ lack of confidence was further apparent in their self-rated knowledge of the topic on arrival to the workshop, by the end of the session, these scores had improved in every case (Beeston et al., 2016).

It is clear from the statistics that more work to encourage women and girls is needed in the UK as well as elsewhere. UK national and international publication patterns, for instance, look very similar. We found that female-led contributions to DMRN meetings averaged around 12% of all contributions in the period 2011 to 2015 (Beeston et al., 2016), comparable to the 14% level reported internationally at recent ISMIR conferences (Hu et al., 2016). Indeed, since so few girls have been applying to study music technology in recent years (Born and Devine, 2015) or have been following careers in related industries (see e.g. female:pressure’s recent reports), a lot of energy is being spent now, worldwide, on discussions of gender and diversity in our field.

Being one of many women with an interest in both music and technology, I am of course very happy to add my own energy to this movement. But on a personal level, I felt somewhat underqualified to tell this story: I have worked with sound all my life, not with questions of gender and diversity! Nonetheless, I felt it was important to present our work at DMRN – speaking to a room comprised mostly of men – since we otherwise risk the issue being viewed as a ‘women’s problem’ rather than a problem to be tackled by our research community as a whole.

I hope therefore that our DMRN presentation will provide a useful starting point for a fruitful discussion about what the UK research community as a whole can do to help provide greater support for women and girls both entering and staying in this field. Furthermore, I am pleased to share our story with the international community too via this WiMIR blogpost, and hope that the community-building approach we have followed with the Yorkshire Sound Women Network may provide a useful model for others to adopt in order to increase the participation of women and girls in sound and music technology in other localities.


Born, G. and Devine, K. (2015). Music technology, gender, and class: Digitization, educational and social change in Britain. Twentieth-Century Music, 12(02), 135–172.

Hu, X., Choi, K., Lee, J. H., Laplante, A., Hao, Y., Cunningham, S. J., & Downie, J. S. (2016). WiMIR – An informetric study on women authors in ISMIR. In Proc. 17th International Society for Music Information Retrieval Conference, 765–771.

Beeston, A.V., Cheesman, L. and Dobson, E. D. (2016). Community-building to support and encourage women and girls in music technology. Digital Music Research Network One-day Workshop (DMRN+11), London, 20 Dec.


Mentoring round 2017 is about to start!

After matching 50 mentees and mentors, we are ready to start the mentoring round in 2017 soon! Happy mentoring!

WiMIR mentoring 2017 participants

Mentoring Program Committee

  • Emilia Gómez, Universitat Pompeu Fabra, Spain
  • Blair Kaneshiro, Stanford University, US
  • Anja Volk, Utrecht University, the Netherlands

Our 50 mentees reside in Australia, China, France, Hong Kong, India, the Netherlands, South Korea, Spain, Turkey, UK, US. They range from high school student to associate professor, and represent a diverse field of interests and backgrounds, such as machine learning, digital signal processing, computer music, computer science, music theory, computational musicology, music psychology, music performance, music and mathematics,  music perception and cognition, computational ethnomusicology, composition, computational neuroscience, digital media, information science and human computer interaction.

We thank our generous mentors for dedicating their time to this program:

  • Jack Atherton, CCRMA, Music Department, Stanford University, US
  • Ana M. Barbancho, Universidad de Málaga, Spain
  • Isabel Barbancho, Universidad de Malaga, Spain
  • Juan Pablo Bello, New York University, US
  • Ching-Wei Chen, Spotify, US
  • Ching-Hua Chuan, University of North Florida, US
  • Andrea Cogliati, University of Rochester, US
  • Tom Collins, Lehigh University, US
  • Sally Jo Cunningham, Waikato University, New Zealand
  • Georgi Dzhambazov, Universitat Pompeu Fabra, Spain
  • Douglas Eck, Google Brain, US
  • Deborah Egan, DINA, UK
  • Dan Ellis, Columbia University and Google, US
  • Philippe Esling, IRCAM, France
  • Ichiro Fujinaga, McGill University, Canada
  • Mathieu Giraud, CNRS, Université de Lille, France
  • Emilia Gómez, Universitat Pompeu Fabra, Spain
  • Fabien Gouyon, Pandora, US
  • Ryan Groves, self-employed MIR Consultant, Germany
  • Dorien Herremans, Queen Mary University of London, UK
  • Xiao Hu, University of Hong Kong, Hong Kong
  • Eric Humphrey, Spotify, US
  • Berit Janssen, Meertens Insitute, Amsterdam, the Netherlands
  • Blair Kaneshiro, Stanford University, US
  • Thor Kell, Spotify, US
  • Katerina Kosta, Queen Mary University of London/Jukedeck, UK
  • Robin Laney, Open University, UK
  • Audrey Laplante, Université de Montréal, Canada
  • Edward Large, University of Connecticut, US
  • Jin Ha Lee, University of Washington, US
  • Alexander Lerch, Georgia Institute of Technology, US
  • David Lewis, University of Oxford, UK
  • Cynthia Liem, Delft University of Technology, the Netherlands
  • Brian McFee, New York University, US
  • David Meredith, Aalborg University, Denmark
  • Emilio Molina, BMAT, Spain
  • Meinard Mueller, International Audio Laboratories Erlangen, Germany
  • Oriol Nieto, Pandora, US
  • Dimitri Papageorgiou, Aristotle University of Thessaloniki, Greece
  • Preeti Rao, IIT–Bombay, India
  • Iris Ren, Utrecht University, the Netherlands
  • Spencer Russell, MIT Media Lab, US
  • Justin Salamon, New York University, US
  • Markus Schedl, Johannes Kepler University Linz, Austria
  • Sertan Şentürk, Universitat Pompeu Fabra, Spain
  • Amina Shabbeer, Amazon Music, US
  • Jeffrey Smith, Smule, US
  • Jordan Smith, AIST, Japan
  • Ajay Srinivasamurthy, Idiap Research Institute, Switzerland
  • Mi Tian, Queen Mary University of London, UK
  • Derek Tingle, SoundCloud, US
  • Doug Turnbull, Ithaca College, US
  • George Tzanetakis, University of Victoria, Canada
  • Rafael Valle, Center for New Music and Audio Technologies, US
  • Makarand Velankar, MKSSS’s Cummins College of Engineering, Pune, India
  • Gissel Velarde, Aalborg University, Denmark
  • Vladimir Viro, Peachnote GmbH, Germany
  • Anja Volk, Utrecht University, the Netherlands
  • Luwei Yang, Queen Mary University London, UK
  • Eva Zangerle, University of Innsbruck, Austria

WiMIR exciting news

WiMIR group is quite active at the moment!!!

  • WiMIR now has an official Twitter account, @Women_MIR. Please follow us to receive updates on the WiMIR mentoring program, ISMIR travel grants, and other initiatives supporting diversity in the field. Feel free to direct tweets to @Women_MIR as well, and we will spread the word!
  • We are starting the next round of our mentoring program, and we are looking for mentors and mentees to sign up before December 11th. More info in our mentoring program page.
  • Iris Ren and Julia Wilkins joined WiMIR as student volunteers, welcome to the team!
  • Our WiMIR representatives at ISIMIR 2017: Jin Ha Lee, Preeti Rao, and Zhongzhe Xiao More details here.


The WiMIR team


“WiMIR mentorship programme” by Iris Yuping Ren, one of our mentees

Post by Iris Yuping Ren, one of the mentees of our mentoring program about her experience:

Thanks to Anja Volk who invited me to write about my experience on the WIMIR mentorship programme. I’m Iris Yuping Ren, a PhD student at the University of Rochester. I play the violin for fun and I studied mathematics and complex system science for my Bachelor and Masters. I’m now working in the Audio Information Research (AIR) lab in the Electrical and Computer Engineering (ECE) department. You can find out more about me here.

I still remember that, when I was signing up for this programme, I was 80% excited and curious about:

  • What is a mentorship programme? (since I’ve never been in one)
  • What kind of person will be my mentor?
  • How will the programme help me?
  • etc.

but also 20% uncertain about whether I should be involved

  • Will there be extra workload for me?
  • What if the conversations go wrong?
  • etc.

Taking a weighted average of the pros and cons, I decided to join anyway! And now I’m glad that I did that.

After filling in the sign-up sheet for the programme, I got an email about a few weeks later. I was assigned a mentor: Oriol Nieto, Scientist at Pandora. I was filled with joy: I like Pandora very much! I wanted to know more about the company, more about what research they do that made this guy choose the company and be choosen by them. Plus, the Committee was very considerate in the introduction email, providing a set of questions for us to talk about. I felt silly that I worried about the nothing-to-talk-about-first-time-Skyping embarrassment.

Oriol and I were then in contact, and had our first Skype a few days later. I was amazed by how the conversation was just flowing between us: from basic introduction to academical questions to considerations for the future. An hour of Skyping felt short! And that doesn’t happen much.

Till now, Oriol and I have had 4 very nice sessions over Skype. Sometimes there are glitches from the internet connections (that’s about all I can complain about), but every time I had such a great time chatting and learning with him. I could write the details of each Skype session, but I guess it won’t offer much since they differ a lot from other mentors and mentees. But I think a more common thing is that I feel lots of support from a knowledgeable and experienced someone who works in the same field and cares about more things than just their work. I can’t speak for everybody, but it was great for me to experience that!

New-to-ISMIR paper mentoring program

We are excited to announce that the New-to-ISMIR paper mentoring program will be active also for this year’s conference as a part of the Diversity & Inclusion (D&I) initiatives!

The New-to-ISMIR paper mentoring program is designed for members new to the ISMIR conference (early stage researchers in MIR or researchers from allied fields who wish to consider submitting their work to an ISMIR conference) to share their advanced-stage work-in-progress ISMIR paper drafts with senior members of the ISMIR community (mentors) to obtain focused reviews and constructive feedback. The program supplements the generic submission guidelines. The program is being run in 2023 closely aligned with the ISMIR 2023 paper submission deadlines.

The topics of the mentored papers are expected to be in alignment with those of ISMIR conferences. We strongly encourage the mentored papers to be revised based on the feedback and submit to the upcoming ISMIR 2023 conference. All papers submitted to ISMIR 2023, whether mentored or not, will go through the regular scientific review process without any exceptions. 

How do I apply?

If you are interested and eligible, please apply to the program by Mar 2, 2023, using the form: https://forms.gle/LdH7HtfQ6tLuNzJcA (please fill in one form for each paper).


Additional details about the program, topics, eligibility, expectations, timeline, and FAQ are available at https://ismir2023.ismir.net/diversity/mentoring or you can contact the organizer at ismir2023-diversity@ismir.net if you have any further questions. 

Sharing science: the MIP-frontiers video communication project

Originally published at https://mip-frontiers.eu/ on July 28, 2021 by Giorgia Cantisani.

Sharing science

Sharing your research with the rest of the world can be very challenging. Sometimes you may need to target a broader audience than simply the colleagues in your particular research field. Colleagues in other communities or disciplines are already less likely to read about your work. When it comes to sharing your research with the general public, things become even more difficult. 

There are several reasons why we all should aim to disseminate our research beyond our universities and scientific communities. For instance, it might be essential to explain your research to a general audience because you are doing it thanks to some public funding. In such a case, it is a social duty to inform the citizens about your findings and make your research comprehensible. It’s a virtuous circle that produces culture and participation, and in return, can pay for new investments in research. 

Another reason is to attract the next generation towards science and your specific research field. This is an aspect that is often underrated because it hasn’t an immediate economic and/or social recognition return, but that is critical in the long term. Undergraduate students can orient their education choices and be our future colleagues and enlarge our research community. It’s vital then to let them know that your research exists and might be interesting for them. This would also benefit and increase diversity in the community and reach all those students for whom computer science is not among the options because of societal, demographic, or socioeconomic factors. 

In this context, it is still tough for scientists to involve the uninitiated on very specific topics that seem to have almost no connection with their everyday lives. However, many different techniques, tools, and languages have been studied and gradually refined over time. With the increasing amount of information available online, it is becoming more and more important to be concise and attract the audience’s attention from the very beginning. Video might be one of the ways to go.

Number of views per day (log) x video length (min). Plot courtesy of “Communicating Science With YouTube Videos: How Nine Factors Relate to and Affect Video Views” by Velho et al. (https://www.frontiersin.org/articles/10.3389/fcomm.2020.567606/full).

Videos about science

Videos about science have become more and more popular over the last decade as they are a low-barrier medium to communicate ideas efficiently and effectively. Short videos from 3 to 5 minutes are ideal because they are long enough to explain a concept and sufficiently short for viewers to decide if they are interested. We all have learned about the advantages and disadvantages of this medium during the last year of the pandemic. The format of the conferences has changed, and video abstracts are now a standard. However, video abstracts are intended for peers and not for a broader audience. When disseminating science, complex concepts should be made accessible for the largest audience possible. In such a case, motion graphics and animated storytelling can be a possible solution. Through the process of abstraction in an animated representation, we can effectively simplify the concept we want to transmit. The style, colour palette, transitions, aesthetic and functional choices can all concur to convey the main message.

Examples of scientific dissemination projects. Image courtesy of Scienseed.

Now, I can’t say this process of abstraction is easy. It takes time, many iterations over the script and many drafts before coming up with something good. You have to learn to work with visual designers who do not know anything about your research. We experienced this when working on the MIP-frontiers video communication project, meant to attract young researchers in our research field. It’s very hard to simplify and abstract things you work on every day. It feels like sacrificing many details which are essential to you for the sake of simplicity. Because of that, you have to always keep in mind who’s your target audience. In the specific case of this video, there was an additional problem: we needed to cover the most possible areas in music information processing (MIP), which was quite hard. The trick we found was to trace back the history of a song that an imaginary inhabitant of the future is listening to. We managed to derive a circular story following the song from composition to recording and from distribution to the user experience. Therefore, the music is the backbone of the video, and its choice was crucial.


When preparing a motion graphic, you need to provide to the visual designers a script (description of the scenes), the voiceover (text that an actor needs to read and which describes the scene), and the background music. With those three elements, the visual designers built an animation on which you can then give feedback and adapt the voiceover and the music again. This process is reiterated repeatedly until convergence, when everyone is happy with the result.

Draft of the initial script of the MIP-frontiers animation.

In our case, an additional difficulty was that the music wasn’t just some “background” music. It was, on the contrary, the absolute protagonist that mainly contributes to conveying the main message. The music evolves throughout the video and changes according to the MIR application we wanted to illustrate. All of this needs a not negligible effort of synchronization and composition.

Regarding the voiceover, we quickly realized how few words can fit a 3-minutes-long video. More importantly, we learned how hard it can be to summarize the vast diversity of research in our community. Moreover, there are synchronization constraints that impose a fixed number of words to express complex concepts. In the end, we reached a compromise trying to represent as extensively as possible some MIP applications.

Once the voiceover, the animation and the music are done, it is not trivial to create the final video anyway. In fact, in addition to a temporal synchronization of events, automation on the volume of the various instruments and the voice are necessary. This operation is always necessary for video production, and the role of a sound engineer is essential for an optimal result. Especially in this work, where music and its evolving parts are the protagonists, this professional figure had a particularly central role in glueing all the components.

Special thanks

In general, it was a great experience! I learned a lot, and I’ve spent some time doing something that is not strictly related to my research, but that is a fundamental part of the scientist job. We really thank Mandela (music) and Scienseed (animation) and Alberto Di Carlo (sound engineer) for their great work!

Mandela is an Italian instrumental jazz band from Vicenza. The sound of the band is characterized by a fusion of jazz idioms, rock, world music, psychedelic, and funk. Over the years, the band has performed in several festivals and venues and released 3 full-length albums. These recordings are all available on the major streaming service. Their last release was presented at the festival Rimusicazioni (Bolzano, Italy) and consists of an original soundtrack for “Grass: A Nation’s Battle for Life” — one of the earliest documentaries ever produced (1925).

For this video, the track Simple from the album Mandela s.t. was used. The song was remixed and remastered by Alberto Di Carlo.

Scienseed is a multifunctional agency for the dissemination of scientific findings. Its founding goal is to promote public engagement in science through all available tools in the Era of IT. We are specialized in the translation of scientific data into different accessible products and activities, aimed at either the scientific community (peers) or the general public (society). We provide support to academic laboratories, research institutes, universities and private institutions to raise public awareness and increase the repercussion of their contribution to science.

Giorgia Cantisani is a PhD student at Télécom Paris in France within the Audio Data Analysis and Signal Processing (ADASP) team and the European training network MIP-Frontiers. Her research interests range from music information retrieval (MIR) to neuroscience. In particular, she is interested in the analysis of brain responses to music and how these can be used to guide and inform music source separation.

Diversity and Inclusion Initiatives at ISMIR 2021

Originally published at https://ismir2021.ismir.net/blog/diversity_inclusion/ on September 5, 2021 by Blair Kaneshiro, Jordan B. L. Smith, Jin Ha Lee, and Alexander Lerch.

The 22nd International Society for Music Information Retrieval Conference (ISMIR2021) is excited to announce a number of Diversity & Inclusion (D&I) initiatives for this year’s conference. These initiatives are aimed toward ensuring a positive and supportive conference environment while also supporting a diverse range of presenters and attendees across backgrounds, career stages, and MIR research areas. This year’s efforts, facilitated by the online format of ISMIR2021, expand upon the numerous Women in Music Information Retrieval (WiMIR) initiatives that have taken place at ISMIR conferences over the past decade, and represent a broadening of how the MIR community views and supports D&I in the field.

This year’s D&I efforts are led by ISMIR2021 D&I Chairs Blair Kaneshiro (Stanford University, US) and Jordan B. L. Smith (ByteDance/TikTok, UK) in close collaboration with the ISMIR2021 General Chairs Jin Ha Lee (University of Washington, US) and Alexander Lerch (Georgia Institute of Technology, US), but it is the efforts of all the ISMIR2021 Organizers that make these initiatives possible. In this blog post we summarize the various D&I initiatives planned for ISMIR2021.

Code of Conduct

Since 2018, a Code of Conduct has accompanied the ISMIR conference. It is prepared by the conference organizers in conjunction with the ISMIR Board and is intended to ensure that the conference environment — whether in person or virtual — is a safe and inclusive space for all participants. In 2020 the Code of Conduct was updated for the first ever virtual ISMIR. All ISMIR2021 participants agree, at time of registration, to adhere to this year’s Code of Conduct.

Registration fees and financial support

To maximize the accessibility of the ISMIR2021 conference for students, the student registration fee is only $15 USD at the early-bird rate (until September 30) and $25 USD thereafter; and the student tutorial fee is just $5. These low rates are subsidized by generous ISMIR2021 sponsor contributions and full (non-student) registrations.

In addition to reduced registration fees, ISMIR2021 offers registration waivers and childcare support to a broad range of attendees. The ISMIR conference has a long history of offering student travel grants to cover conference registration and lodging. Since 2016, the conference has offered WiMIR grants as well, which provide financial assistance to women of any career stage to attend the conference. The ISMIR2019 conference expanded financial support opportunities once more to include Community grants for former and prospective MIR community members, and the ISMIR2020 conference offered childcare grants as well as Black in MIR registration waivers for the first time.

This year, the low cost of attending the conference, combined with generous sponsor support, enables the ISMIR2021 conference to once again provide a wide range of grants. Registration grants are available to students, unaffiliated attendees (anyone who has no professional affiliation that will cover the registration fee), and to attendees who self-identify with a broad range of D&I categories including Black in MIR, attendees from low- or middle-income countries, “New to ISMIR” presenter, Queer in MIR, and WiMIR. In addition, any attendee is eligible to apply for a childcare grant.

Details about ISMIR2021 grant eligibility and the application process are available here: https://bit.ly/ismir2021grants

D&I blog posts

This year’s D&I initiatives also seek to address the “hidden curriculum” of navigating academia as well as STEM research. To this end, the ISMIR2021 organizers are authoring a number of blog posts on such topics as preparing a successful ISMIR submission and reviewing ISMIR papers, as well as reposting relevant content from the WiMIR blog. Upcoming blog posts will include an introduction to ISMIR2021 Newcomer Initiatives and community advice on navigating the conference. Visit the ISMIR2021 blog page (maintained by Qhansa Bayu (Social Media Chair; Telkom University, ID) and Ashvala Vinay (Website Chair; Georgia Institute of Technology, US)) to stay up to date!

Special call for papers on “Cultural Diversity in MIR”

This year, the conference organizers wanted to promote the cultural diversity of the ISMIR community and its research. To this end, the ISMIR2021 Call for Papers included a special call, for papers on “Cultural Diversity in MIR”. This year’s Scientific Chairs — Zhiyao Duan (University of Rochester, US), Juhan Nam (KAIST, KR), Preeti Rao (IIT Bombay, IN), and Peter van Kranenburg (Meertens Institute, NL) — organized the track with a focus on non-Western music and cross-cultural studies. Submissions to this track underwent the same review process as papers in the main track, with specially selected meta-reviewers.

In all, 44 papers were submitted to this track, of which 11 were accepted and verified by the Scientific Chairs to match the call. Accepted papers in this track will be presented in the same format as other accepted papers, with recognition on the conference website and the institution of a special paper award for the themed track.

Special Late-Breaking/Demo (LBD) “New to ISMIR” track

The Late-Breaking/Demo (LBD) session, involving short-format papers which undergo light peer review, has long served as a venue for new or junior researchers to gain a foothold in the MIR community. The ISMIR2021 LBD chairs — Li Su (Academia Sinica, TW), Chih-Wei Wu (Netflix, US), and Siddharth Gururani (Electronic Arts, US) — present a new special track called “New to ISMIR”. In this track, first-time ISMIR attendees, students, WiMIR community members, and underrepresented minorities have the opportunity to receive extra mentoring on their LBD submissions. Presenters in this track are strongly encouraged to apply for a registration waiver as well. More information can be found in the full Call for LBDs.

Newcomer Initiatives

Navigating a new conference can be challenging in the best of times, but is especially difficult in the virtual format. The ISMIR2021 Newcomer Initiatives Chairs — Nick Gang (Apple, US) and Elona Shatri (Queen Mary University of London, UK) — are organizing a number of initiatives to help newcomers navigate the conference; meet other attendees; and establish social and professional connections to help them achieve their academic, research, and career aims during and beyond the conference. Announcements on these initiatives are coming soon!

WiMIR Sponsorship

Since 2016, industry sponsors have contributed specifically to WiMIR, typically by funding WiMIR travel grants and/or hosting WiMIR-themed receptions during the conference. These initiatives increase access to the ISMIR conference for women of all career stages, and also provide a designated setting for women and other attendees to network during the conference.

We express our sincere thanks to this year’s WiMIR sponsors, whose contributions support the various D&I initiatives described here, and to the ISMIR2021 Sponsorship Chairs: Sertan Şentürk (Kobalt Music, UK), Alia Morsi (Universitat Pompeu Fabra, ES), and Lamtharn “Hanoi” Hantrakul (ByteDance/TikTok, CN).

If your company would like to participate as a WiMIR sponsor, more information can be found on the ISMIR2021 Call for Sponsors page.

WiMIR Plenary Session

WiMIR began meeting informally at ISMIR conferences starting at ISMIR2011. After a few years of ad-hoc meetings organized by interested attendees, a WiMIR plenary session was incorporated into the main ISMIR conference program starting in 2015. Since then, WiMIR sessions have included presentations on the WiMIR Mentoring Program as well as community and invited keynote presentations. This year’s WiMIR plenary session will include an invited keynote speaker to be announced soon!

WiMIR Meetup Sessions

While the virtual conference format has posed challenges when it comes to offering the range and serendipity of interactions experienced in person, it also offers opportunities to try out new formats to bring attendees together — not only for formal research presentations, but also for informal discussions. Last year, the ISMIR2020 conference for the first time included WiMIR-themed meetup sessions throughout the conference. These sessions, centered around the theme of “Notable Women in MIR”, gave conference attendees the chance to meet informally with women in the field and discuss topics ranging from career paths to technical details of their research.

This year, the ISMIR2021 conference is expanding upon the format of these sessions to include a range of underrepresented communities in MIR. More information on these special meetup sessions will be announced in coming months.

WiMIR Workshop

The WiMIR Workshop has taken place annually since 2018 as a satellite event of the ISMIR conference. The goal of the WiMIR Workshop is to provide a venue for mentorship, networking, and collaboration among women and allies in the ISMIR community. The Workshop took place as an in-person one-day event in 2018 and again in 2019, and migrated to a virtual format in 2020 due to the COVID-19 pandemic.

In 2021, the WiMIR 4th Annual Workshop will take place virtually on Friday, October 29 and Saturday, October 30. It is a free event open to all members of the MIR community, and will include events for all time zones. The speaker lineup and schedule will be announced soon!

Other ISMIR Community D&I Initiatives

The D&I initiatives of ISMIR2021 are part of a larger ecosystem of ISMIR community initiatives. For more information on these initiatives, and to stay up to date on what is happening with the ISMIR2021 conference and the community at large, visit the following resources:

See you at ISMIR2021 in November!

Blair Kaneshiro (Stanford University, USA) and Jordan B. L. Smith (ByteDance, UK) are the Diversity & Inclusion Chairs of the ISMIR2021 Conference. Jin Ha Lee (University of Washington, USA) and Alexander Lerch (Georgia Institute of Technology, USA) are the General Chairs of the ISMIR2021 Conference. ISMIR2021 will take place as a virtual conference from November 4-8, 2021.