AdMIRe 2012: 4th International Workshop on Advances in Music Information Research

AdMIRe 2012: 4^th International Workshop on Advances in Music Information Research: "The Web of Music"

in conjunction with the 21^st International World Wide Web Conference

Location: Lyon, France
Date: 17^th April 2012

supported by the EU-FP7 project Music Information ReSearch (MIReS)

Location & Time: Salon P. Tête d'Or 1 (9:00 - 17:35)

> Proceedings

> News
> Motivation
> Program
> Call for Papers
> Committee
> Submit Paper
> Contact

> AdMIRe 2011, AdMIRe 2010, AdMIRe 2009

The International Workshop on Advances in Music Information Research (AdMIRe) serves as a forum for theoretical and practical discussions of cutting edge research on Web technologies for music information research. Topics covered include Web mining for music information extraction, retrieval, and recommendation as well as mobile applications and services that make use of Web 2.0 technology. Submissions addressing concrete implementations of systems and services by both academic institutions and industrial companies are also welcome.

News

2012-05-02: Photos of presentations online

2012-04-16: Slight modifications of workshop program. We will start at 9 am! Proceedings available

2012-03-09: Second keynote will be given by Xavier Serra; workshop program available

2012-01-11: Deadlines extended

2012-01-10: Keynote will be given by Francesco Ricci

2011-12-22: Extended versions of outstanding papers will be published in a Special Issue of the International Journal of Multimedia Information Retrieval

2011-10-05: Website relaunched

Motivation

Music information research has been a fast growing field of research during the past decade. In traditional MIR, music-related information were extracted from the audio signal using signal processing techniques. These methods, however, cannot capture semantic information that is not encoded in the audio signal, but nonetheless essential to many consumers, e.g., the meaning of the lyrics of a song or the political motivation or background of a singer. The recent launches of Google Music, Amazon.com’s Cloud Player and Apple’s iCloud with iTunes Match show the huge commercial interest behind music distribution and consumption. Given the fact that music is an omnipresent topic on the Web, techniques to mine the Web of Music are vital for music information research and related applications.

In recent years, the emergence of various Web 2.0 platforms and services dedicated or related to the music and audio domain, like last.fm, YouTube, MusicBrainz, Pandora, or echonest, has been providing novel and powerful, albeit noisy, sources for high level, semantic information on music artists, albums, songs, and others. The abundance of such information provided by the power of the crowd can therefore contribute to music information research and development considerably. On the other hand, the wealth of newly available, semantically meaningful information offered on Web 2.0 platforms also poses new challenges, e.g., dealing with the huge amount and the noisiness of this kind of data, various user biases, hacking, or the cold start problem.

Another recent trend are innovative user interfaces to access the large amounts of music available on smart mobile devices that are always connected to the Web. Dealing with the vast amounts of music requires new interaction paradigms and intelligent services that provide, for example, personalized and context-aware music recommendations. The current emergence and confluence of these challenges make this an interesting field for researchers and industry practitioners alike.

Program

Technical Program

9:00 - 9:05	Opening Remarks
9:05 - 10:00	Keynote by Francesco Ricci > Context-Aware Music Recommender Systems
10:00 - 10:30	Session: Music Retagging Using Label Propagation and Robust Principal Component Analysis (1 paper) Yi-Hsuan Yang, Dmitry Bogdanov, Perfecto Herrera, and Mohamed Sordo > Music Retagging Using Label Propagation and Robust Principal Component Analysis
10:30 - 11:00	Coffee Break
11:00 - 12:30	Session: Content-based Music Processing (3 papers) Justin Salamon, Joan Serrà, and Emilia Gómez > Melody, Bassline and Harmony Representations for Music Version Identification Martin Haro, Joan Serrà, Álvaro Corral, and Perfecto Herrera > Power-law distribution in encoded MFCC frames of speech, music, and environmental sound signals Andrew Hankinson, John Ashley Burgoyne, Gabriel Vigliensoni, and Ichiro Fujinaga > Creating Large-Scale Searchable Digital Collections from Printed Music Materials
12:30 - 14:00	Lunch Break
14:00 - 14:45	Keynote by Xavier Serra > Data Gathering for a Culture Specific Approach in MIR
14:45 - 15:45	Session: Challenges and Evaluation (2 papers) Brian McFee, Thierry Bertin-Mahieux, Daniel P.W. Ellis, and Gert Lanckriet > The Million Song Dataset Challenge Julián Urbano and Markus Schedl > Towards Minimal Test Collections for Evaluation of Audio Music Similarity and Retrieval
15:45 - 16:00	Coffee Break
16:00 - 17:30	Session: Similarity and Recommendation (3 papers) Marcos Aurélio Domingues, Fabien Gouyon, Alípio Mário Jorge, José Paulo Leal, João Vinagre, Luís Lemos, and Mohamed Sordo > Combining Usage and Content in an Online Music Recommendation System for Music in the Long-Tail Daniel Wolff and Tillman Weyde > Adapting Similarity on the MagnaTagATune Dataset: Effects of Model and Feature Choices Markus Schedl and David Hauger > Mining Microblogs to Infer Music Artist Similarity and Cultural Listening Patterns
17:30 - 17:35	Concluding Remarks

Keynotes

Francesco Ricci

Free University of Bozen-Bolzano, Italy

Context-Aware Music Recommender Systems

Abstract:
Recommender Systems (RSs) are software tools and techniques providing suggestions for items to be of use to a user. The context of an item usage, e.g., when or in which physical environment a music track is played, can influence the user’s emotional response and evaluation for the item. Hence, Music Recommender Systems should take into account this information to deliver more useful (perceived) recommendations. Context modeling and context-dependent reasoning is a complex subject and still there are major technical and practical difficulties to solve: obtain sufficient and reliable data describing the user preferences in context; selecting the right context information, i.e., relevant in a particular personalization task; understanding the impact of the contextual dimensions on the personalization process; embedding the contextual dimensions in a recommendation computational model. These topics will be illustrated in the talk, making examples taken from the music recommender systems that we have developed.

Biography:
Francesco Ricci is an associate professor of computer science at the Free University of Bozen-Bolzano, Italy. His current research interests include recommender systems, intelligent interfaces, mobile systems, machine learning, case-based reasoning, and the applications of ICT to tourism. He has published more than one hundred of academic papers on these topics. He is on the editorial board of Journal of Information Technology & Tourism and the Journal of User Modeling and User Adapted Interaction. He is member of the steering committee of the ACM Conference on Recommender Systems. He served on the program committees of several conferences, including as a program co-chair of the ACM Conference on Recommender Systems (RecSys), the International Conference on Case-Based Reasoning (ICCBR) and the International Conference on Information and Communication Technologies in Tourism (ENTER).

Xavier Serra

Universitat Pompeu Fabra, Barcelona, Spain

Data Gathering for a Culture Specific Approach in MIR

Abstract:
In this presentation I will describe the data gathering work done within a large research project, CompMusic, which emphasizes a culture specific approach in the automatic description of several world music repertoires. Currently we are focusing on the Hindustani (North India), Carnatic (South India) and Turkish-makam (Turkey) music traditions. The selection and organization of the data to be processed for the characterization of each of these traditions is of the utmost importance.

Biography:
Xavier Serra is Associate Professor of the Department of Information and Communication Technologies and Director of the Music Technology Group at the Universitat Pompeu Fabra in Barcelona. After a multidisciplinary academic education he obtained a PhD in Computer Music from Stanford University in 1989 with a dissertation on the spectral processing of musical sounds that is considered a key reference in the field. His research interests cover the understanding, modelling and generation of musical signals by computational means, with a balance between basic and applied research and approaches from both scientific/technological and humanistic/artistic disciplines. Dr. Serra is very active in promoting initiatives in the field of Sound and Music Computing at the local and international levels, being involved in the editorial board of a number of journals and conferences and giving lectures on current and future challenges of the field. He has recently been awarded an Advanced Grant of the European Research Council to carry out the project CompMusic aimed at promoting multicultural approaches in music computing research.

Call for Papers

The Call for Papers is available as HTML and as PDF.

AdMIRe 2012 solicits regular technical papers of up to 10 pages following the ACM author guidelines as well as short papers of up to 5 pages. Paper submissions must be original and not submitted to or accepted by any other conference or journal, regardless of the paper type (regular or short). We will invite authors of particularly outstanding submissions to publish extended versions in a Special Issue of the International Journal of Multimedia Information Retrieval.

All submissions to this workshop will be peer-reviewed by at least three Program Committee members. The review process will be double-blind.

Topics of Interest

Music Information Systems

Multimodal User Interfaces

User Modeling, Personalization, Music Recommendation

Context-aware and Mobile Music Information Retrieval

Music in the Cloud

Web Mining and Information Extraction

Collaborative Tags, Social Media Mining, (Social) Network Analysis

Semantic Content Analysis and Music Indexing

Hybrid Approaches using Context and Content

Large-Scale Music Similarity Measurement, Scalability Issues and Solutions

Evaluation, Mining of Ground Truth and Data Collections

Semantic Web, Linked Data, Ontologies, Semantics and Reasoning

Mining and Analysis of Music Video Clips, Music-Related Images and Artwork

Important Dates

Abstract Submisson	2012-01-22
Full Paper Submission	2012-01-29
Notification of Results	2012-02-29
Camera Ready Submission	2012-03-09

Workshop Committee

Organizers and Program Chairs

Markus Schedl	Department of Computational Perception, Johannes Kepler University, Linz, Austria
Peter Knees	Department of Computational Perception, Johannes Kepler University, Linz, Austria
Òscar Celma	Gracenote, Emeryville, CA, USA

Program Committee

Mathieu Barthet	Queen Mary University of London, UK
Stephan Baumann	German Research Center for AI, Kaiserslautern, Germany
Dmitry Bogdanov	Universitat Pompeu Fabra, Barcelona, Spain
Ching-Wei Chen	Gracenote, Emeryville, CA, USA
Mehdi Elahi	University of Bolzano-Bozen, Italy
Benjamin Fields	Musicmetric, London, UK
Arthur Flexer	Austrian Research Institute for Artificial Intelligence, Vienna, Austria
Emilia Gómez	Universitat Pompeu Fabra, Barcelona, Spain
Masataka Goto	National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan
Fabien Gouyon	Institute for Systems and Computer Engineering of Porto, Portugal
Xiao Hu	University of Denver, CO, USA
Noam Koenigstein	School of Electrical Engineering, Tel Aviv University, Tel Aviv, Israel
Ian Knopke	BBC, London, UK
Paul Lamere	the echonest, Davis Square, Somerville, MA, USA
Matthias Mauch	last.fm, London, UK
Robert Macrae	SoundHound, San Jose, CA, USA
Brian McFee	University of San Diego, CA, USA
Mitsunori Ogihara	University of Miami, FL, USA
Dominik Schnitzer	Austrian Research Institute for Artificial Intelligence, Vienna, Austria
Malcolm Slaney	Yahoo! Research Laboratory, Silicon Valley, CA, USA
Mohamed Sordo	Universitat Pompeu Fabra, Barcelona, Spain
Sebastian Stober	Otto-von-Guericke-Universität Magdeburg, Germany
Steve Tjoa	Imagine Research, San Francisco, CA, USA
Julián Urbano	University Carlos III of Madrid, Spain
Arjen de Vries	Centrum Wiskunde & Informatica (CWI), Amsterdam, the Netherlands
Jun Wang	Dolby Laboratories, Beijing, P.R. China
Geraint Wiggins	Queen Mary University of London, UK

Submit Paper

Submissions will be managed by EasyChair. Please create a user account if you have not already done so, login and follow the instructions to submit a new paper.

Contact

Markus Schedl
Department of Computational Perception
Johannes Kepler University (JKU) Linz
Altenberger Str. 69, A-4040 Linz, Austria

Tel: +43 732 2468 1512
Fax: +43 732 2468 1520
E-Mail: markus dot schedl at jku dot at

last edited by ms on 2012-05-02