International Journal of Computer Engineering in Research Trends

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Music Genre Classification Using MFCC, K-NN and SVM Classifier

Nilesh M. Patil, Dr. Milind U. Nemade, , ,

Affiliations
Ph.D Research Scholar1, Pacific Academy of Higher Education and Research University, Udaipur, India.

:10.22362/ijcert/2017/v4/i2/xxxx [UNDER PROCESS]

Abstract

The audio corpus available today on Internet and Digital Libraries is increasing rapidly in huge volume. We need to properly index them if we want to have access to these audio data. The search engines available in market also find it challenging to classify and retrieve the audio files relevant to the userâ€™s interest. In this paper, we describe an automated classification system model for music genres. We firstly found good feature for each music genre. To obtain feature vectors for the classifiers from the GTZAN genre dataset, features like MFCC vector, chroma frequencies, spectral roll-off, spectral centroid, zero-crossing rate were used. Different classifiers were trained and used to classify, each yielding varying degrees of accuracy in prediction.

Citation

Nilesh M. Patil et.al, â€œMusic Genre Classification Using MFCC, K-NN and SVM Classifierâ€, International Journal Of Computer Engineering In Research Trends, 4(2):43-47, February-2017.

Keywords : Music, MFCC, K-NN, SVM, GTZAN dataset.

References

[1]	G. Tzanetakis, P. Cook, â€œMusical genre classification of audio signalsâ€, IEEE Transactions on Speech and Audio Processing, Vol. 10, Issue 5, July 2002.
[2]	Chandsheng Xu, Mc Maddage, Xi Shao, Fang Cao, and Qi Tan, â€œMusical genre classification using support vector machinesâ€, IEEE Proceedings of International Conference of Acoustics, Speech, and Signal Processing, Vol. 5, pp. V-429-32, 2003.
[3]	N. Scaringella, G. Zoia, and D. Mlynek, â€œAutomatic genre classification of music content: a surveyâ€, IEEE Signal Processing Magazine, Vol. 23, Issue 2, pp. 133â€“141, 2006.
[4]	Jan WÃ¼lfing and Martin Riedmiller, â€œUnsupervised learning of local features for music classificationâ€ ISMIR, pp. 139â€“144, 2012.
[5]	Sox.sourceforge.net. Sox - sound exchangeâ€” homepage, 2015.
[6]	http://marsyas.info/downloads/datasets.html

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Citation Index

Citations Indices	All
Citations	1026
h-index	14
i10-index	20
Source: Google Scholar

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DOI:10.22362/ijcert

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