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