Aggregate features and ADABOOST for music classification-Reference-Cited by-同舟云学术

Aggregate features and ADABOOST for music classification

Published:2006-06-30 Issue:2-3 Volume:65 Page:473-484
ISSN:0885-6125
Container-title:Machine Learning
language:en
Short-container-title:Mach Learn

Author:

Bergstra James,Casagrande Norman,Erhan Dumitru,Eck Douglas,Kégl Balázs

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

http://link.springer.com/content/pdf/10.1007/s10994-006-9019-7.pdf

Reference32 articles.

1. Ahrendt, P., & Meng, A. (2005). Music Genre Classification using the multivariate AR feature integration model. Extended Abstract. MIREX genre classification contest (www.music-ir.org/evaluation/mirex-results).

2. Aucouturier, J., & Pachet, F. (2002). Music Similarity Measures: Whats the Use?. In: Fingerhut, M. (ed.): Proceedings of the Third International Conference on Music Information Retrieval (ISMIR 2000).

3. Aucouturier, J., & Pachet, F. (2003). Representing musical genre: A state of the art. Journal of New Music Research 32(1), 1–12.

4. Bello, J., Daudet, L., Abdallah, S., Duxbury, C., Davies, M., & Sandler, M. (2005). A Tutorial on Onset Detection in Music Signals. IEEE Transactions on Speech and Audio Processing.

5. Bergstra, J., Casagrande, N., & Eck, D. (2005a). Artist Recognition: A Timbre- and Rhythm-Based Multiresolution Approach. MIREX artist recognition contest.

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