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
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;
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
DOI :
10.1109/ICCIS.2010.307
