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Multiclass Suport Class Support Vector Machine for Music Genre Classification
International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 107 - Number 19
Year of Publication: 2014
|
10.5120/18858-9368 |
Nimesh Prabhu, Ashvek Asnodkar and Rohan Kenkre. Article: Multiclass Suport Class Support Vector Machine for Music Genre Classification. International Journal of Computer Applications 107(19):15-17, December 2014. Full text available. BibTeX
@article{key:article,
author = {Nimesh Prabhu and Ashvek Asnodkar and Rohan Kenkre},
title = {Article: Multiclass Suport Class Support Vector Machine for Music Genre Classification},
journal = {International Journal of Computer Applications},
year = {2014},
volume = {107},
number = {19},
pages = {15-17},
month = {December},
note = {Full text available}
}
Abstract
Musical genres are defined as categorical labels that auditors use to characterize pieces of music sample. A musical genre can be characterized by a set of common perceptive parameters. An automatic genre classification would actually be very helpful to replace or complete human genre annotation, which is actually used. SVM have found overwhelming success in the area of pattern recognition. Finally we validate proposed algorithm with experimental results.
References
- G. Tzanetakis and P. Cook, "Musical Genre Classification of Audio Signals" In IEEE Trans. Acoust. Speech, Signal Processing , vol. 10, ,N°5, July 2002.
- G. Tzanetakis and P. Cook, "Audio analysis using the discrete wavelet transform" in Proc. Conf. Acoustics and Music Theory Applications, Sept. 2001.
- T. Heitolla, "Automatic Classification of music signals ", Master of Science Thesis, February 2003.
- R. Duda, P. Hart and D. Stork, "Pattern Classification" , John Wiley & Son, New York, 2000.