Contributions to Books:
A. Rauber, E. Pampalk, W. Merkl:
"Content-based Music Indexing and Organization";
in: "Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2002)",
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
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
Created from the Publication Database of the Vienna University of Technology.