Music Genre Classification using Deep Neural Networks

Authors

  • G. Jawaherlalnehru  Research Scholar Department of Computer Science & Engineering, Annamalai University, Chidambaram, Tamil Nadu, India
  • S. Jothilakshmi  Assistant Professor Department of Information Technology, Annamalai University, Chidambaram, Tamil Nadu, India

Keywords:

Music Information Retrieval, Music genre classification, Deep learning, Mel frequency cepstral coefficients.

Abstract

Music genres can be defined as categorical labels created by humans to identify or characterize the style of music. This work presents a comprehensive machine learning approach to the problem of automatic musical genre classification using the audio signal. The system is developed using a Deep Neural Network (DNN) to recognize the genres. Mel Frequency Cepstral Coefficients (MFCC) features are used to represent the music characteristics. The system is evaluated with MIR datasets. The proposed system observed higher classification accuracy of 97.8%.

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2018-04-30

Issue

Volume 4, Issue 4, March-April-2018

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
G. Jawaherlalnehru, S. Jothilakshmi, " Music Genre Classification using Deep Neural Networks, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 4, pp.935-940, March-April-2018.