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
Subject: Metadata for Audio

Click to purchase paper as a non-member or you can login as an AES member to see more options.

No AES members have commented on this paper yet.

Subscribe to this discussion

To be notified of new comments on this paper you can subscribe to this RSS feed. Forum users should login to see additional options.

Start a discussion!

If you would like to start a discussion about this paper and are an AES member then you can login here:
Username:
Password:

If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.