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dc.contributor.authorWan, Vincent
dc.contributor.authorRenals, Steve
dc.date.accessioned2006-05-18T17:26:24Z
dc.date.available2006-05-18T17:26:24Z
dc.date.issued2003
dc.identifier.citationIn Proc. IEEE ICASSP, volume 2, pages 221-224, 2003.en
dc.identifier.urihttp://hdl.handle.net/1842/1132
dc.description.abstractSupport vector machines with the Fisher and score-space kernels are used for text independent speaker verification to provide direct q discrimination between complete utterances. This is unlike approaches such as discriminatively trained Gaussian mixture models or other discriminative classifiers that discriminate at the frame-level only. Using the sequence-level discrimination approach we are able to achieve error-rates that are significantly better than the current state-of-the-art on the PolyVar database.en
dc.format.extent170465 bytes
dc.format.extent190804 bytes
dc.format.mimetypeapplication/octet-stream
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherIEEE Signal Processing Societyen
dc.subjectspeechen
dc.titleSVMSVM: Support vector machine speaker verification methodology.en
dc.typeConference Paperen


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