Content-based Music Indexing and Organization
      Andreas Rauber(1), Elias Pampalk(2), Dieter Merkl(1)

           (1) Dept. of Software Technology
               Vienna Univ of Technology
               A-1040 Vienna, Austria
               {andi, dieter}@ifs.tuwien.ac.at

           (2) Austrian Research Institute for Artificial Intelligence
               A-1010 Vienna, Austria
               elias@ai.univie.ac.at


Abstract:

While electronic music archives are gaining popularity, access to and 
navigation within these archives is usually limited to text-based queries 
or manually predefined genre category browsing.
We present a system that automatically organizes a music collection 
according to the perceived sound similarity resembling genres or styles of 
music.
Audio signals are processed according to psychoacoustic models to obtain a 
time-invariant representation of its characteristics.
Subsequent clustering provides an intuitive interface where similar pieces 
of music are grouped together on a map display.

Category: H.5.5 - Information systems - Sound and Music Computing
Category: H.3.1 - Information Systems - Information Storage and Retrieval
                  [content analysis and indexing]
 
Keywords: Music Retrieval, Genre, Rhythm, Psychoacoustic  Models, 
Clustering, Self-Organizing Map, Neural Networks

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Proceedings of the 25. Annual International ACM SIGIR Conference on 
Research and Development in Information Retrieval (SIGIR 02)
August 11-15, 2002, Tampere, Finland
http://www.ifs.tuwien.ac.at/ifs/research/publications.html