A SVM ¨C Based Classification Approach to Musical Audio

dc.contributor.author	Namunu Chinthaka Maddage	en_US
dc.contributor.author	Changsheng Xu	en_US
dc.contributor.author	Ye Wang	en_US
dc.contributor.editor	Holger H. Hoos	en_US
dc.contributor.editor	David Bainbridge	en_US
dc.date.accessioned	2004-10-21T04:26:37Z
dc.date.available	2004-10-21T04:26:37Z
dc.date.issued	2003-10-26	en_US
dc.identifier.isbn	0-9746194-0-X	en_US
dc.identifier.uri	http://jhir.library.jhu.edu/handle/1774.2/43
dc.description.abstract	This paper describes an automatic heirarchical music classification approach based on support vector machines (SVM). Based on the proposed method, the music is classified into coursed classes such as vocal, instrumental or vocal mixed with instrumental music. These main classes are further sub-classed according to gender and instrument type. A novel method, Correction Algorithm for Music Sequence (CAMS) has been developed to imporve the classification efficiency.	en_US
dc.format.extent	331124 bytes
dc.format.mimetype	application/pdf
dc.language.iso	en_US
dc.publisher	Johns Hopkins University	en_US
dc.subject	Music Analysis	en_US
dc.subject	Audio	en_US
dc.title	A SVM ¨C Based Classification Approach to Musical Audio	en_US
dc.type	Article	en_US