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.
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 Suite—bit.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.
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 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 email@example.com.
Mentoring Session I (intros and big picture)
Mentoring Session II (deep dive into the topic)
We look forward to seeing you at the Women in Music Information Retrieval 1st Annual Workshop!
The WiMIR Workshop Organizers
- Blair Kaneshiro, Stanford University
- Katherine M. Kinnaird, Brown University/Smith College
- Eric J. Humphrey, Spotify
- Thor Kell, Spotify
Abstract submission form here: https://goo.gl/forms/hy3ygYnKKS9fTLa13
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
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!
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!
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
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 firstname.lastname@example.org and email@example.com 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!
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.
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 firstname.lastname@example.org
We look forward to your response and commitment to continuing the mentoring program!
Emilia Gómez, Blair Kaneshiro, and Anja Volk (WiMIR Mentoring Program Committee)
We are looking forward to the next WiMIR session at ISMIR conference in Suzhou, kindly organized by our WiMIR co-chairs:
Jin Ha Lee
University of Washington,
Indian Institute of Technology Bombay,
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: