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An approach of genetic programming for music emotion classification

  • Intelligent and Information Systems
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Abstract

In this paper, we suggest a new approach of genetic programming for music emotion classification. Our approach is based on Thayer’s arousal-valence plane which is one of representative human emotion models. Thayer’s plane which says human emotions is determined by the psychological arousal and valence. We map music pieces onto the arousal-valence plane, and classify the music emotion in that space. We extract 85 acoustic features from music signals, rank those by the information gain and choose the top k best features in the feature selection process. In order to map music pieces in the feature space onto the arousal-valence space, we apply genetic programming. The genetic programming is designed for finding an optimal formula which maps given music pieces to the arousal-valence space so that music emotions are effectively classified. k-NN and SVM methods which are widely used in classification are used for the classification of music emotions in the arousal-valence space. For verifying our method, we compare with other six existing methods on the same music data set. With this experiment, we confirm the proposed method is superior to others.

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Correspondence to Jee-Hyong Lee.

Additional information

Recommended by Editor Young-Hoon Joo.

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (No. 2013-0458-000) and IT R&D program of MKE/KEIT (10041244, Smart TV 2.0 Software Platform).

Sung-Woo Bang received his M.S. degree in the Department of Electrical and Computer Engineering from Sungkyunkwan University, Suwon, Korea, in 2011. He is currently a counselor in LG CTS, Seoul, Korea. His current interest fields are web-based inference and intelligent systems.

Jaekwang Kim received his B.S. and M.S. degrees from Sungkyunkwan University, Suwon, Korea in 2004, and 2006, respectively. His research interests include networks, security, and intelligent systems. He is currently a Ph.D. student at the Department of Electrical and Computer. Engineering, Sungkyunkwan University, He received the best presentation paper award at ICUIMC, Suwon, Korea in Jan. 2009.

Jee-Hyong Lee received his M.S. and Ph.D. degrees in Computer Science from Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea, in 1995 and 1999, respectively. He was an international fellow at SRI International, California from 2000 to 2001. He has been working as a faculty at Sungkyunkwan University, Suwon, Korea since March 2002. His current interest fields are web intelligence and intelligent information processing.

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Bang, SW., Kim, J. & Lee, JH. An approach of genetic programming for music emotion classification. Int. J. Control Autom. Syst. 11, 1290–1299 (2013). https://doi.org/10.1007/s12555-012-9407-7

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