AdMIRe: INTERNATIONAL WORKSHOP ON ADVANCES IN MUSIC INFORMATION RESEARCH 2009
SAN DIEGO, CALIFORNIA
14 -16 DECEMBER 2009
CALL FOR PAPERS
http://www.cp.jku.at/conferences/admire2009/
In Conjunction with the IEEE International Symposium on Multimedia 2009
The International Workshop on Advances in Music Information Research (AdMIRe) 2009 will serve as a forum for theoretical and practical discussions of cutting edge research in the fields of Web mining for music information extraction, retrieval, and recommendation as well as in mobile applications and services. Research on multimodal extraction, retrieval, and presentation with a focus on the music and audio domain is especially welcome.
So are submissions addressing concrete implementations of systems and services by both academic institutions and industrial companies. Workshop papers will be official publications of IEEE, which will be included in IEEEXplore and also be printed as part of the conference proceedings.
MOTIVATION:
Music information retrieval (MIR) as a subfield of multimedia information retrieval has been a fast growing field of research during the past decade. In traditional MIR research, 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.
In recent years, the emergence of various Web 2.0 platforms and services dedicated to the music and audio domain, like last.fm, MusicBrainz, or Discogs, 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 MIR 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, not at last addressable to platforms like Apple's iPhone or Google's Android, are intelligent user interfaces to access the large amounts of music usually available on today's mobile music players and the corresponding services. Mobile devices that offer high speed Web access allow for even more music to be consumed via Web services. Dealing with these vast amounts of music requires intelligent services on mobile devices 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.
TOPICS OF INTEREST:
Music Information Systems
Multimodal User Interfaces
Context-aware Music Applications
User Modeling and Personalization
Social Networks and Collaborative Tagging in the Music and Audio Domain
Web Mining and Information Extraction in the Music Domain
Combination of Web-based and Signal-based Information Extraction Methods
Music Recommendation
Semantic Web, Linking Open Data and Open Web Services for the Music and Audio Domain
Ontologies, Semantics and Reasoning in the Music and Audio Domain
Evaluation, Mining of Ground Truth and Data Collections
Music Indexing and Retrieval Techniques
Exploration and Discovery in Large Music Collections
Multimodal Semantic Content Analysis
ORGANIZERS:
Markus Schedl Department of Computational Perception,
Johannes Kepler University, Linz, Austria
Òscar Celma Barcelona Music and Audio Technologies,
Barcelona, Spain
Peter Knees Department of Computational Perception,
Johannes Kepler University, Linz, Austria
Tim Pohle Department of Computational Perception,
Johannes Kepler University, Linz, Austria
PROGRAM COMMITTEE:
Jean-Julien Aucouturier Temple University, Japan Campus, Tokyo, Japan
Luke Barrington University of California, San Diego, CA, USA
Stephan Baumann German Research Center for AI, Kaiserslautern, Germany
Gijs Geleijnse Philips Research Laboratories, Eindhoven, the Netherlands
Emilia Gómez Music Technology Group, Universitat Pompeu Fabra, Barcelona, Spain
Fabien Gouyon Institute for Systems and Computer
Engineering of Porto, Porto, Portugal
Paul Lamere the echonest, Davis Square, Somerville, MA, USA
Elias Pampalk last.fm, London, UK
Jeremy Pickens FX Palo Alto Laboratory, Palo Alto, CA, USA
Yves Raimond BBC Audio & Music Interactive, London, UK
Andreas Rauber Department of Software Technology and
Interactive Systems, Vienna University of Technology, Vienna, Austria
Dominik Schnitzer Austrian Research Institute for Artificial Intelligence, Vienna, Austria
Douglas Turnbull Department of Computer Science, Swarthmore College, Swarthmore, PA, USA
Gerhard Widmer Department of Computational Perception,
Johannes Kepler University, Linz, Austria
IMPORTANT DATES:
Full Paper Submission Deadline: July 20, 2009
Notification of Results: August 30, 2009
Camera Ready Submission: September 25, 2009
SAN DIEGO, CALIFORNIA
14 -16 DECEMBER 2009
CALL FOR PAPERS
http://www.cp.jku.at/conferences/admire2009/
In Conjunction with the IEEE International Symposium on Multimedia 2009
The International Workshop on Advances in Music Information Research (AdMIRe) 2009 will serve as a forum for theoretical and practical discussions of cutting edge research in the fields of Web mining for music information extraction, retrieval, and recommendation as well as in mobile applications and services. Research on multimodal extraction, retrieval, and presentation with a focus on the music and audio domain is especially welcome.
So are submissions addressing concrete implementations of systems and services by both academic institutions and industrial companies. Workshop papers will be official publications of IEEE, which will be included in IEEEXplore and also be printed as part of the conference proceedings.
MOTIVATION:
Music information retrieval (MIR) as a subfield of multimedia information retrieval has been a fast growing field of research during the past decade. In traditional MIR research, 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.
In recent years, the emergence of various Web 2.0 platforms and services dedicated to the music and audio domain, like last.fm, MusicBrainz, or Discogs, 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 MIR 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, not at last addressable to platforms like Apple's iPhone or Google's Android, are intelligent user interfaces to access the large amounts of music usually available on today's mobile music players and the corresponding services. Mobile devices that offer high speed Web access allow for even more music to be consumed via Web services. Dealing with these vast amounts of music requires intelligent services on mobile devices 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.
TOPICS OF INTEREST:
Music Information Systems
Multimodal User Interfaces
Context-aware Music Applications
User Modeling and Personalization
Social Networks and Collaborative Tagging in the Music and Audio Domain
Web Mining and Information Extraction in the Music Domain
Combination of Web-based and Signal-based Information Extraction Methods
Music Recommendation
Semantic Web, Linking Open Data and Open Web Services for the Music and Audio Domain
Ontologies, Semantics and Reasoning in the Music and Audio Domain
Evaluation, Mining of Ground Truth and Data Collections
Music Indexing and Retrieval Techniques
Exploration and Discovery in Large Music Collections
Multimodal Semantic Content Analysis
ORGANIZERS:
Markus Schedl Department of Computational Perception,
Johannes Kepler University, Linz, Austria
Òscar Celma Barcelona Music and Audio Technologies,
Barcelona, Spain
Peter Knees Department of Computational Perception,
Johannes Kepler University, Linz, Austria
Tim Pohle Department of Computational Perception,
Johannes Kepler University, Linz, Austria
PROGRAM COMMITTEE:
Jean-Julien Aucouturier Temple University, Japan Campus, Tokyo, Japan
Luke Barrington University of California, San Diego, CA, USA
Stephan Baumann German Research Center for AI, Kaiserslautern, Germany
Gijs Geleijnse Philips Research Laboratories, Eindhoven, the Netherlands
Emilia Gómez Music Technology Group, Universitat Pompeu Fabra, Barcelona, Spain
Fabien Gouyon Institute for Systems and Computer
Engineering of Porto, Porto, Portugal
Paul Lamere the echonest, Davis Square, Somerville, MA, USA
Elias Pampalk last.fm, London, UK
Jeremy Pickens FX Palo Alto Laboratory, Palo Alto, CA, USA
Yves Raimond BBC Audio & Music Interactive, London, UK
Andreas Rauber Department of Software Technology and
Interactive Systems, Vienna University of Technology, Vienna, Austria
Dominik Schnitzer Austrian Research Institute for Artificial Intelligence, Vienna, Austria
Douglas Turnbull Department of Computer Science, Swarthmore College, Swarthmore, PA, USA
Gerhard Widmer Department of Computational Perception,
Johannes Kepler University, Linz, Austria
IMPORTANT DATES:
Full Paper Submission Deadline: July 20, 2009
Notification of Results: August 30, 2009
Camera Ready Submission: September 25, 2009
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