DocumentCode :
1929676
Title :
Content-based music classification
Author :
Lo, Yu-lung ; Lin, Vi-Chang
Author_Institution :
Dept. of Inf. Manage., Chaoyang Univ. of Technol., Taichung, Taiwan
Volume :
2
fYear :
2010
fDate :
9-11 July 2010
Firstpage :
112
Lastpage :
116
Abstract :
The music classification techniques can be discriminated into two categories - based by music content-based classification and training by learning machine classification. Both have their advantages and disadvantages. For music content-based classifications, most of the approaches are based on single music feature, such as melody or chord, and the accuracy is up to 70% in few genres of music. However, the accuracy for classification of most music genres is lower. In this paper, we study the features of music content and use the multiple features of music data to improve the accuracy of music classification. Our performance studies shown that the higher accuracy can be achieved for classification of classical music by using multiple features of music content for classification.
Keywords :
content-based retrieval; learning (artificial intelligence); music; pattern classification; content-based music classification; learning machine classification; Indexes; content-based retrieval; digital music; multimedia database; music classification; music database;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-5537-9
Type :
conf
DOI :
10.1109/ICCSIT.2010.5563642
Filename :
5563642
Link To Document :
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