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dc.contributor.authorWei-Ho Tsaien_US
dc.contributor.authorHsin-Min Wangen_US
dc.contributor.authorDwight Rodgersen_US
dc.contributor.authorShi-Sian Chengen_US
dc.contributor.authorHung-Min Yuen_US
dc.contributor.editorHolger H. Hoosen_US
dc.contributor.editorDavid Bainbridgeen_US
dc.date.accessioned2004-10-21T04:26:30Z
dc.date.available2004-10-21T04:26:30Z
dc.date.issued2003-10-26en_US
dc.identifier.isbn0-9746194-0-Xen_US
dc.identifier.urihttp://jhir.library.jhu.edu/handle/1774.2/24
dc.description.abstractThis 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.format.extent426714 bytes
dc.format.mimetypeapplication/pdf
dc.languageenen_US
dc.language.isoen_US
dc.publisherJohns Hopkins Universityen_US
dc.subjectIR Systems and Algorithmsen_US
dc.subjectDigital Librariesen_US
dc.titleBlind Clustering of Popular Music Recordings Based on Singer Voice Characteristicsen_US
dc.typearticleen_US


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