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Music Genre Classification Using Data Mining and Machine Learning

  • Nimesh Ramesh Prabhu
  • James Andro-Vasko
  • Doina Bein
  • Wolfgang Bein
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 738)

Abstract

With accelerated advances in internet technologies users make listen to a staggering amount of multimedia data available worldwide. Musical genres are descriptions that are used to characterize music in music stores, radio stations and now on the Internet. Music choices vary from person to person, even within the same geographical culture. Presently Apple’s iTunes and Napster classify the genre of each song with the help of the listener, thus manually. We propose to develop an automatic genre classification technique for jazz, metal, pop and classical using neural networks using supervised training which will have high accuracy, efficiency and reliability, and can be used in media production house, radio stations etc. for a bulk categorization of music content.

Keywords

Automatic classification Data mining Machine learning Music genre 

Notes

Acknowledgements

Doina Bein acknowledges the support by Air Force Office of Scientific Research under award number FA9550–16–1-0257.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Nimesh Ramesh Prabhu
    • 1
  • James Andro-Vasko
    • 2
  • Doina Bein
    • 1
  • Wolfgang Bein
    • 2
  1. 1.Department of Computer ScienceCalifornia State University, FullertonFullertonUSA
  2. 2.Department of Computer ScienceUniversity of NevadaLas VegasUSA

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