Content-based classification of music using VQ-multifeature clustering technique

Authors:
Won-Jung Yoon;Kyu-Sik Park
Affiliations:
Division of Information and Computer Science, Dankook University, Seoul, Korea;Division of Information and Computer Science, Dankook University, Seoul, Korea
Venue:
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Year:
2005

Citing 3
Cited 1

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IEEE MultiMedia
A comparative study on content-based music genre classification

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Fuzzy declustering-based vector quantization

Pattern Recognition

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Abstract

A new content-based music genre classification algorithm using VQ-Multifeature clustering method is proposed in this paper. In order to alleviate the system uncertainty problem due to the different query patterns and query lengths, a new robust feature extraction method so called VQ-Multifeature clustering with feature selection is proposed. Effectiveness of the proposed system is verified in terms of the system stability and the classification results with SVM pattern classifier.