Valued researcher, developer, colleague,
This is to let you know that the paper submission deadline for the
AdMIRe 2011 workshop is approaching. Please find a detailed Call-for-Papers
below. We are looking forward to your contribution, if your time and
scope of interest permits! We hope to see you in Barcelona.
Best regards,
Markus Schedl
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++ AdMIRe 2011: 3rd International Workshop on ++
++ Advances in Music Information Research ++
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http://www.cp.jku.at/conferences/AdMIRe2011/
In Conjunction with the
IEEE International Conference on Multimedia and Expo (ICME)
Barcelona, Spain, July 11-15, 2011
Tentative Date of the Workshop: July 15, 2011
Paper Submission: February 20, 2011
The "International Workshop on Advances in Music Information Research"
(AdMIRe) serves 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 IEEE Xplore and also be printed as part of the conference
proceedings.
Motivation:
-----------
Music information research has been a fast growing field during the past
decade. In traditional content-based MIR, music-related information
was 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
echonest, has provided 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
hence 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, 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. 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
+ Mining and Analysis of Music Video Clips
+ Mining and Analysis of Music-Related Images / Artwork
+ Mining and Analysis of Music Video Clips
+ Mining and Analysis of Music-Related Images / Artwork
+ Music Recommendation
+ Semantic Web, Linking Open Data and Open Web Services for Music/Audio
+ Ontologies, Semantics and Reasoning in the Music and Audio Domain
+ Similarity Measurement
+ Evaluation, Mining of Ground Truth and Data Collections
+ Music Information Retrieval, Services, and Applications for Mobile Devices
+ Music Indexing and Retrieval Techniques
+ Exploration and Discovery in Large Music Collections
+ Multimodal Semantic Content Analysis
Program Chairs:
---------------
Markus Schedl Dept. of Computational Perception, JKU Linz, Austria
Ňscar Celma Barcelona Music and Audio Technologies, Spain
Peter Knees Dept. of Computational Perception, JKU Linz, Austria
Publicity Chair:
----------------
Noam Koenigstein School of Electrical Engineering, Tel Aviv
University, Israel
Program Committee:
------------------------------
Amélie Anglade Queen Mary University, London, UK
Stephan Baumann German Research Center for AI, Kaiserslautern,Germany
Benjamin Fields Dept. of Computing, Goldsmiths' College, University
of London, UK
Gijs Geleijnse Philips Research Laboratories, Eindhoven, the Netherlands
Emilia Gómez Music Technology Group, Universitat Pompeu Fabra,
Barcelona, Spain
Masataka Goto Advanced Industrial Science and Technology (AIST),
Tsukuba, Japan
Fabien Gouyon Institute for Systems and Computer Engineering of
Porto, Portugal
Kurt Jacobson the echonest, Davis Square, Somerville, MA, USA
Noam Koenigstein School of Electrical Engineering, Tel Aviv
University, Israel
Paul Lamere the echonest, Davis Square, Somerville, MA, USA
Tim Pohle Johannes Kepler University, Linz, Austria
Yves Raimond BBC Audio& Music Interactive, London, UK
Andreas Rauber Vienna University of Technology, Austria
Dominik Schnitzer Austrian Research Institute for Artificial
Intelligence, Vienna
Malcolm Slaney Yahoo! Research Laboratory, Silicon Valley, CA, USA
Mohamed Sordo Music Technology Group, Universitat Pompeu Fabra,
Barcelona, Spain
Sebastian Stober Otto-von-Guericke-Universität Magdeburg, Germany
Jun Wang Dolby Laboratories, Beijing, P.R. China
Geraint Wiggins Dept. of Computing, Goldsmiths' College, London, UK
Important Dates:
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Full Paper Submission: February 20, 2010
Notification of Results: April 10, 2011
Camera Ready Submission: April 20, 2011
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++ http://www.cp.jku.at/conferences/AdMIRe2011/ ++
++++++++++++++++++++++++++++++++++++++++++++++++++
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