Multimedia Information Retrieval: Music and Audio

Tutorial Slide:

Tutorial Slides available here:


Music is an omnipresent topic in our daily lives, as almost everyone enjoys listening to his or her favorite tunes. Music information retrieval (MIR) is a research field that aims, among other things, at automatically extracting semantically meaningful information from various representations of music entities, such as a digital audio file, a song’s lyrics, or a tweet about a microblogger’s current listening activity.

Given the recent incorporation of music and audio topics in ACM Multimedia, the intended half-day tutorial aims at (i) explaining standard and state-of-the-art techniques for music content description, (ii) reporting on the basics and the state of-the-art in mining music-related information from the web and social media to infer context-based features, and (iii) demonstrating attractive applications based on MIR technologies (using both content- and context-based methods).

The main goal is to give a sound and comprehensive, nevertheless easy-to-understand, introduction to the scientific use of multimedia data sources in the music domain. The presented approaches are highly valuable for tasks and applications such as automatic music video analysis and generation, music-synchronized computer graphics, automated music playlist generation, personalized web radio music recommendation systems, and intelligent user interfaces to music. Therefore, attendees will leave the tutorial with a concise conception of how to mine music-relevant data and build such applications. Furthermore, the tutorial should also promote the field of Music Information Retrieval to the multimedia community.


Dr. Markus Schedl

Markus Schedl is an Assistant Professor at the Department of Computational Perception at the Johannes Kepler University Linz. He graduated in Computer Science from the Vienna University of Technology. He earned his Ph.D. in Computational Perception from the Johannes Kepler University Linz. Markus further studied International Business Administration at the Vienna University of Economics and Business Administration as well as at the Handelshögskolan of the University of Gothenburg, which led to a Master’s degree. His main research interests include web and social media mining, information retrieval, multimedia, music information research, and user interfaces.

Markus (co-)authored 80 refereed conference papers and journal articles (among others, published in ACM Multimedia, SIGIR, ECIR, IEEE Visualization; Journal of Machine Learning Research, ACM Transactions on Information Systems, Springer Information Retrieval, IEEE Multimedia). Furthermore, he serves on various program committees and reviewed submissions to several conferences and journals (among others, ACM Multimedia, ECIR, IJCAI, ICASSP, IEEE Visualization; IEEE Transactions of Multimedia, Elsevier Data & Knowledge Engineering, ACM Transactions on Intelligent Systems and Technology, Springer Multimedia Systems).

Since 2007, Markus has been giving several lectures, among others, “Music Information Retrieval”, “Exploratory Data Analysis”, “Multimedia Search and Retrieval” and “Learning from User-generated Data”. He further spent several guest lecturing stays at the Universitat Pompeu Fabra, Barcelona, Spain, the Utrecht University, the Netherlands, the Queen Mary, University of London, UK, and the Kungliga Tekniska Högskolan, Stockholm, Sweden.

Dr. Emilia Gomez

Emilia Gomez is a post-doctoral researcher and assistant professor at the Music Technology Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra (UPF), Barcelona, Spain. She graduated as a Telecommunication Engineer specialized in Signal Processing at Universidad de Sevilla. Then, she received a DEA in Acoustics, Signal Processing and Computer Science applied to Music (ATIAM) at IRCAM, Paris. In July 2006, she completed her Ph.D. in Computer Science and Digital Communication at the UPF, on the topic of Tonal Description of Music Audio Signals (awarded by EPSON foundation). She has  been visiting researcher at the Royal Institute of Technology, Stockholm and Centre for Interdisciplinary Research in Music Media and Technology, McGill University, Montreal.

Her research interests deal with understanding the way humans listen to music, and building computational models capable of providing meaningful descriptions of music audio signals. She has been working on melodic and tonal description of music recordings, music similarity and classification, computer-assisted music analysis and computational ethnomusicology.

As of January 2013, her scientific indicators include more than 90 peer-reviewed publications and more than 1,300 citations (h-index=18) according to Google Scholar. She has participated in different research projects funded by the EC, Spanish and Canadian institutions, and she acts as a reviewer of the main journals and scientific events in the field of Music Information Retrieval. She has taken part in the organization of many scientific events, e.g. PC member (ISMIR 2004-2012). She is member of several committees, e.g IEEE member, AES TC on Semantic Audio and has been invited speaker in diverse events, e.g. keynote speaker at the Folk Music analysis Workshop (Amsterdam, June 2013) and invited speaker at the Sound and Music Computing Conference (Stockholm, August 2013).

Dr. Masataka Goto

Masataka Goto received the Doctor of Engineering degree from Waseda University in 1998. He is currently a Prime Senior Researcher and the Leader of the Media Interaction Group at the National Institute of Advanced Industrial Science and Technology (AIST), Japan. In 1992 he was one of the first to start work on automatic music understanding, and has since been at the forefront of research in music technologies and music interfaces based on those technologies. Since 1998 he has also worked on speech recognition interfaces, and since 2006 he has developed web services based on content analysis and crowdsourcing ( and He serves concurrently as a Visiting Professor at the Institute of Statistical Mathematics, an Associate Professor (Cooperative Graduate School Program) in the Graduate School of Systems and Information Engineering, University of Tsukuba, and a Project Manager of the Exploratory IT Human Resources Project (MITOH Program) run by the Information Technology Promotion Agency (IPA).

Over the past 21 years, Masataka Goto has published more than 190 papers in refereed journals and international conferences and has received 34 awards, including several best paper awards, best presentation awards, and the Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology (Young Scientists’ Prize). He has served as a committee member of over 80 scientific societies and conferences and was the Chair of the IPSJ (Information Processing Society of Japan) Special Interest Group on Music and Computer (SIGMUS) in 2007 and 2008 and the General Chair of the 10th International Society for Music Information Retrieval Conference (ISMIR 2009). In 2011, as the Research Director he began a 5-year research project (OngaCREST Project) on music technologies, a project funded by the Japan Science and Technology Agency (CREST, JST).

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