Blind Clustering of Popular Music Recordings Based on Singer Voice Characteristics

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dc.contributor.author Wei-Ho Tsai en_US
dc.contributor.author Hsin-Min Wang en_US
dc.contributor.author Dwight Rodgers en_US
dc.contributor.author Shi-Sian Cheng en_US
dc.contributor.author Hung-Min Yu en_US
dc.contributor.editor Holger H. Hoos en_US
dc.contributor.editor David Bainbridge en_US
dc.date.accessioned 2004-10-21T04:26:30Z
dc.date.available 2004-10-21T04:26:30Z
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/1774.2/24
dc.description.abstract This paper presents an effective technique for automatically clustering undocumented music recordings based on their associated singer. This serves as an indispensable step towards indexing and content-based information retrieval of music by singer. The proposed clustering system operates in an unsupervised manner, in which no prior information is available regarding the characteristics of singer voices, nor the population of singers. Methods are presented to separate vocal from non-vocal regions, to isolate the singers' vocal characteristics from the background music, to compare the similarity between singers' voices, and to determine the total number of unique singers from a collection of songs. Experimental evaluations conducted on a 200-track pop music database confirm the validity of the proposed system. en_US
dc.description.provenance Made available in DSpace on 2004-10-21T04:26:30Z (GMT). No. of bitstreams: 1 paper.pdf: 426714 bytes, checksum: dec0d495673a1eb2e26be213a43cb25e (MD5) Previous issue date: 2003-10-26 en
dc.format.extent 426714 bytes
dc.format.mimetype application/pdf
dc.language en en_US
dc.language.iso en_US
dc.publisher Johns Hopkins University en_US
dc.subject IR Systems and Algorithms en_US
dc.subject Digital Libraries en_US
dc.title Blind Clustering of Popular Music Recordings Based on Singer Voice Characteristics en_US
dc.type article en_US

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