International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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SYMMER: A Systematic Approach to Multiple Musical Emotion Recognition

  • Lee, Jae-Sung (School of Computer Science and Engineering, Chung-Ang University) ;
  • Jo, Jin-Hyuk (School of Computer Science and Engineering, Chung-Ang University) ;
  • Lee, Jae-Joon (School of Computer Science and Engineering, Chung-Ang University) ;
  • Kim, Dae-Won (School of Computer Science and Engineering, Chung-Ang University)
  • Received : 2011.03.28
  • Accepted : 2011.05.18
  • Published : 2011.06.25
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Abstract

Music emotion recognition is currently one of the most attractive research areas in music information retrieval. In order to use emotion as clues when searching for a particular music, several music based emotion recognizing systems are fundamentally utilized. In order to maximize user satisfaction, the recognition accuracy is very important. In this paper, we develop a new music emotion recognition system, which employs a multilabel feature selector and multilabel classifier. The performance of the proposed system is demonstrated using novel musical emotion data.

Keywords

References

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Cited by

  1. Music Emotions Recognition by Machine Learning With Cognitive Classification Methodologies vol.11, pp.4, 2017, https://doi.org/10.4018/IJCINI.2017100105