DocumentCode
2467231
Title
Music Emotion Detecting Based on Beat Spectrum
Author
Li, Yan ; Yang, Shiying ; Li, Wei ; Zhu, Ye
Author_Institution
Lab. of Digital Media Art & Technol., Shanghai Univ., Shanghai, China
fYear
2010
fDate
17-19 Dec. 2010
Firstpage
1245
Lastpage
1248
Abstract
A new method is proposed in this paper to detect emotions in music. Four audio features are used to classify emotions into six clusters with the RAKEL (Random klabelsets)multi-label classification. The Experiments show the rationality of proposed method and good performance on classification with the feature of beat spectrum.
Keywords
audio signal processing; RAKEL multi-label classification; Random klabelsets; audio features; beat spectrum feature; music emotion detecting; Classification algorithms; Data mining; Feature extraction; Mathematical model; Rhythm; audio features extract; multilabel classification; music emotion detecting; music information retrieval; pattern recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational and Information Sciences (ICCIS), 2010 International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-8814-8
Electronic_ISBN
978-0-7695-4270-6
Type
conf
DOI
10.1109/ICCIS.2010.307
Filename
5709507
Link To Document