Abstract

Psychologically, music can affect human mood and influence human behavior. In this paper, a novel method for music mood classification is introduced. In the experiment, music mood classification was performed using feature extraction based on MPEG-7 features from the ISO/IEC 15938 standard for describing multimedia content. The result of this feature extraction are 17 low-level descriptors. Here, we used the Audio Power, Audio Harmonicity, and Audio Spectrum Projection features. Moreover, the discrete wavelet transform (DWT) was utilized for audio signal reconstruction. The reconstructed audio signals were classified by the new method, which uses a support vector machine with a confidence interval (SVM-CI). According to the experimental results, the success rate of the proposed method was satisfactory and SVM-CI outperformed the ordinary SVM.

Original languageEnglish
Article number1850016
JournalInternational Journal on Artificial Intelligence Tools
Volume27
Issue number5
DOIs
Publication statusPublished - 1 Aug 2018

Keywords

  • MPEG-7
  • Music mood classification
  • confidence interval
  • support vector machine

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