Factors in automatic musical genre classification of audio signals

Automatic musical genre classification is an important tool for organizing the large collections of music that are becoming available to the average user. In addition, it provides a structured way of evaluating musical content features that does not require extensive user studies. The paper provides...

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Bibliographic Details
Published in2003 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (IEEE Cat. No.03TH8684) pp. 143 - 146
Main Authors Tao Li, Tzanetakis, G.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2003
Subjects
Audio compression
Bandwidth
Computer science
Feature extraction
Hard disks
Humans
Machine learning
Music information retrieval
Peer to peer computing
Performance analysis
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Summary:Automatic musical genre classification is an important tool for organizing the large collections of music that are becoming available to the average user. In addition, it provides a structured way of evaluating musical content features that does not require extensive user studies. The paper provides a detailed comparative analysis of various factors affecting automatic classification performance, such as choice of features and classifiers. Using recent machine learning techniques, such as support vector machines, we improve on previously published results using identical data collections and features.
ISBN:9780780378506
0780378504
DOI:10.1109/ASPAA.2003.1285840