Organising or browsing music collections in a musically meaningful way calls for tagging the data in terms of e.g. rhythmic, melodic or harmonic aspects, among others. In some cases, such metadata can be extracted automatically from musical files; in others, a trained listener must extract it by hand. In this article, we consider a specific set of rhythmic descriptors for which we provide procedures of automatic extraction from audio signals. Evaluating the relevance of such descriptors is a difficult task that can easily become highly subjective. To avoid this pitfall, we assessed the relevance of these descriptors by measuring their rate of success in genre classification experiments. We conclude on the particular relevance of the tempo and a set of 15 MFCC-like descriptors.

Authors: Dixon, Simon; Pampalk, Elias; Widmer, Gerhard
Affiliations: Universitat Pompeu Fabra, Barcelona, Spain ; Austrian Research Institute for Artifcial Intelligence, Vienna, Austria ; Department of Medical Cybernetics and Artifcial Intelligence, Medical University of Vienna, Austria(See document for exact affiliation information.)
AES Conference: 25th International Conference: Metadata for Audio (June 2004)
Paper Number: 6-2
Publication Date: June 1, 2004 Import into BibTeX
Subject: Metadata for Audio
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=12819

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