Exploiting genre for music emotion classification

Author

Lin, Yu-Ching ; Yang, Yi-Hsuan ; Chen, Homer H. ; Liao, I-Bin ; Ho, Yeh-Chin

Author_Institution

Nat. Taiwan Univ., Taipei, Taiwan

fYear

2009

fDate

June 28 2009-July 3 2009

Firstpage

618

Lastpage

621

Abstract

Genre and emotion have been applied to content-based music retrieval and organization; however, the intrinsic correlation between them has not been explored. In this paper we present a statistical association analysis to examine such intrinsic correlation and propose a two-layer scheme that exploits the correlation for emotion classification. Significant improvement of classification accuracy over the traditional single-layer scheme is obtained.

Keywords

content-based retrieval; correlation methods; music; signal classification; statistical analysis; content-based music organization; content-based music retrieval; intrinsic correlation; music emotion classification; music genre classification; statistical association analysis; two-layer scheme; Content based retrieval; Explosives; Laboratories; Large-scale systems; Mood; Multiple signal classification; Music information retrieval; Predictive models; Rhythm; Telecommunications; Music genre classification; association analysis; music emotion classification;

fLanguage

English

Publisher

ieee

Conference_Titel

Multimedia and Expo, 2009. ICME 2009. IEEE International Conference on

Conference_Location

New York, NY

ISSN

1945-7871

Print_ISBN

978-1-4244-4290-4

Electronic_ISBN

1945-7871

Type

conf

DOI

10.1109/ICME.2009.5202572

Filename

5202572