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ICMCS
2007
IEEE

Music Emotion Classification: A Regression Approach

13 years 10 months ago
Music Emotion Classification: A Regression Approach
Typical music emotion classification (MEC) approaches categorize emotions and apply pattern recognition methods to train a classifier. However, categorized emotions are too ambiguous for efficient music retrieval. In this paper, we model emotions as continuous variables composed of arousal and valence values (AV values), and formulate MEC as a regression problem. The multiple linear regression, support vector regression, and AdaBoost.RT are adopted to evaluate the prediction accuracy. Since the regression approach is inherently continuous, it is free of the ambiguity problem existing in its categorical counterparts.
Yi-Hsuan Yang, Yu-Ching Lin, Ya-Fan Su, Homer H. C
Added 03 Jun 2010
Updated 03 Jun 2010
Type Conference
Year 2007
Where ICMCS
Authors Yi-Hsuan Yang, Yu-Ching Lin, Ya-Fan Su, Homer H. Chen
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