DocumentCode :
2294372
Title :
Music style mining and classification by melody
Author :
Shan, Man-Kwan ; Kuo, Fang-Fei ; Chen, Mao-Fu
Author_Institution :
Dept. of Comput. Sci., Nat. Chengchi Univ., Taipei, Taiwan
Volume :
1
fYear :
2002
fDate :
2002
Firstpage :
97
Abstract :
Music style is one of the features that people used to classify music. Discovery of music style is helpful for the design of a content-based music retrieval system. In this paper we investigate the mining and classification of music style by melody from a collection of MIDI music. We extract the chord from the melody and investigate the representation of extracted features and corresponding mining techniques for music classification. Experimental results show that the classification accuracy is about 70% to 84% for 2-way classification.
Keywords :
content-based retrieval; data mining; electronic music; feature extraction; multimedia databases; music; pattern classification; MIDI music; chord extraction; content-based music retrieval system; extracted feature representation; melody classification; music classification; music style mining; Computer science; Content based retrieval; Data mining; Feature extraction; Hidden Markov models; Humans; Instruments; Monitoring; Multiple signal classification; Music information retrieval;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia and Expo, 2002. ICME '02. Proceedings. 2002 IEEE International Conference on
Print_ISBN :
0-7803-7304-9
Type :
conf
DOI :
10.1109/ICME.2002.1035727
Filename :
1035727
Link To Document :
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