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A Deep Neural Network Model for Music Genre Recognition

  • M. Suero
  • C. P. Gassen
  • D. Mitic
  • N. XiongEmail author
  • M. Leon
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1074)

Abstract

Convolutional neural networks (CNNs) have become increasingly important to deal with many image processing and pattern recognition problems. In order to use CNNs in music genre recognition, spectrograms (visual representation of the spectrum of frequencies of a signal as it varies with time) are usually employed as inputs of the network. Yet some other approaches used music features for genre classification as well. In this paper we propose a new deep network model combining CNN with a simple multi-layer neural network for music genre classification. Since other features are taken into account in the multi-layer network, the combined deep neural network has shown better accuracy than each of the single models in the experiments (Code available at: https://github.com/risengnom/Music-Genre-Recognition.).

Keywords

Music genre classification Multi-layer neural network Convolutional neural network Deep network Mel frequency 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • M. Suero
    • 1
  • C. P. Gassen
    • 1
  • D. Mitic
    • 1
  • N. Xiong
    • 1
    Email author
  • M. Leon
    • 1
  1. 1.Mälardalen UniversityVästeråsSweden

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