Music emotion recognition with consideration of personal preference

Chuan Yu Chang, Chi Keng Wu, Chun Yen Lo, Chi-Jen Wang, Pau-Choo Chung

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

In order to discover the relationship between music and the emotion that it may evoke, twenty-one features have been extracted to describe music. A feature selection algorithm called sequential floating forward selection (SFFS) is utilized to find discriminative features. An estimation of the correlation coefficient was applied to determine features of music that evoke an emotion. These features were then used to train two support vector machines (SVMs) for an individual subject to classify music that evokes happiness, anger, sadness, and peacefulness. Experimental results show that the proposed approach can be used to classify music that evokes an emotion for an individual subject with high classification accuracy.

Original languageEnglish
Title of host publication2011 7th International Workshop on Multidimensional (nD) Systems, nDS 2011
DOIs
Publication statusPublished - 2011 Dec 13
Event2011 7th International Workshop on Multidimensional (nD) Systems, nDS 2011 - Poitiers, France
Duration: 2011 Sep 52011 Sep 7

Publication series

Name2011 7th International Workshop on Multidimensional (nD) Systems, nDS 2011

Other

Other2011 7th International Workshop on Multidimensional (nD) Systems, nDS 2011
CountryFrance
CityPoitiers
Period11-09-0511-09-07

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All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

Cite this

Chang, C. Y., Wu, C. K., Lo, C. Y., Wang, C-J., & Chung, P-C. (2011). Music emotion recognition with consideration of personal preference. In 2011 7th International Workshop on Multidimensional (nD) Systems, nDS 2011 [6076843] (2011 7th International Workshop on Multidimensional (nD) Systems, nDS 2011). https://doi.org/10.1109/nDS.2011.6076843