Music genre classification based on MPEG-7 audio features
Authors: 
Song Li, Haifeng Li, Lin MaAuthors Info & Claims
Song Li, Haifeng Li, Lin MaAuthors Info & ClaimsPages 185 - 188
Abstract
Music genre is a useful tool which can categorize large music database. MPEG-7 is an international standard for managing audiovisual contents. MPEG-7 audio features are used for audio classification, music instrument classification and speech recognition. In this paper, we present a series of experiments to evaluate the MPEG-7 audio features for music genre classification performance. For the feature extraction, we choose Mel-scale Frequency Cepstrum Coefficients (MFCC), Audio Spectrum Envelop (ASE), Audio Spectrum Projection (ASP) and the combination of Audio Spectrum Centroid, Spread and Flatness. Some comparable results are derived from our database consisting of 7 different genres of music with Gaussian Mixture Model (GMM) classifier.
References
[1]
T. Li and M. Ogihara. Music genre classification with taxonomy. In Proc. of IEEE Intern. Conf. on Acoustics, Speech and Signal Processing, pages 197--200, Philadelphia, USA, 2005.
[2]
A. Meng, P. Ahrendt, and J. Larsen. Improving music genre classification by short-time feature integration. In IEEE Intern. Conf. on Acoustics, Speech, and Signal Processing, pages 497--500, Philadelphia, PA, USA, 2005.
[3]
A. Meng, P. Ahrendt, and J. Larsen. Improving music genre classification by short-time feature integration. In IEEE Intern. Conf. on Acoustics, Speech, and Signal Processing, pages 497--500, Philadelphia, PA, USA, 2005.
[4]
M. Mandel, D. Ellis, "Song-Level Features and Support Vector Machine for Music Classification", ISMIR-05, London, 2005.
[5]
J. C. Wang, J. F. Wang, K. W. He, and C. S. Hsu, "Environmental sound classification using hybrid SVM/KNN classifier and MPEG-7 audio low-level descriptor", Proc. IEEE International Joint Conference on Neural Networks, Canada, July 2006, pp. 1731--1735.
[6]
S. Ntalampiras, I. Potamitis, and N. Fakotakis, "Automatic recognition of urban environmental sounds events", Proc. CIP2008, Eurasip, 2008, pp. 110--113.
[7]
H. G. Kim, N. Moreau, and T. Sikora, "Audio classification based on MPEG-7 spectral basis representation," IEEE Trans. Circuits Syst. Video Technol., vol. 14, no. 5, pp. 716--725, May 2004.
Index Terms
- Music genre classification based on MPEG-7 audio features
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Information & Contributors
Information
Published In
December 2010
218 pages
ISBN:9781450304603
DOI:10.1145/1937728
- General Chairs:
- Yong Rui,
- Klara Nahrstedt,
- Xiaofei Xu,
- Program Chairs:
- Hongxun Yao,
- Shuqiang Jiang,
- Jian Cheng
Copyright © 2010 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 30 December 2010
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- Research-article
Funding Sources
- Key Laboratory Opening Funding of MOE-Microsoft Key Laboratory of Natural Language Processing and Speech
- Ministry of Education of the People's Republic of China
- National Natural Science Foundation of China
Conference
ICIMCS '10
ICIMCS '10: The Second International Conference on Internet Multimedia Computing and Service
December 30 - 31, 2010
Harbin, China
Acceptance Rates
Overall Acceptance Rate 163 of 456 submissions, 36%
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