We address the problem of classifying polyphonic musical audio signals by their Meter, as 'binary' or 'ternary'. Experiments have been conducted on a 70 instances database (20s excerpts from commercial songs without particular genre or timbre restriction). The Meter is the number of beats between regularly recurring accents (or Downbeats). Our approach aims to test the hypothesis that acoustic evidences for Downbeats can be measured on the signal; putting a special focus on their temporal recurrences. We experimented several approaches to the problem of feature selection and report some interesting results: measurements of a very small set of beat descriptors (i.e. 4) and subsequent processing (based on descriptors' autocorrelation functions) permit to reach around 95% of correct classification. Using only the temporal centroid, almost 90% of correct classification can be achieved.
Authors:
Gouyon, Fabien; Herrera, Perfecto
Affiliation:
Music Technology Group, IUA-Universitat Pompeu Fabra, Barcelona, Spain
AES Convention:
114 (March 2003)
Paper Number:
5811
Publication Date:
March 1, 2003
Subject:
Analysis and Synthesis of Sound
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.
To be notified of new comments on this paper you can subscribe to this RSS feed. Forum users should login to see additional options.
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.