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dc.contributor.authorAlsaade, F.
dc.contributor.authorMalegaonkar, A.
dc.contributor.authorAriyaeeinia, A.
dc.date.accessioned2008-02-12T16:40:50Z
dc.date.available2008-02-12T16:40:50Z
dc.date.issued2005
dc.identifier.citationAlsaade , F , Malegaonkar , A & Ariyaeeinia , A 2005 , Fusion of cross stream information in speaker verification . in Procs of the 3rd COST 275 Workshop on Biometrics on the Internet . Office for Official Publications of the European Communities , pp. 63-66 .
dc.identifier.isbn92-898-0019-4
dc.identifier.otherPURE: 113548
dc.identifier.otherPURE UUID: 22e9b223-6b58-40bc-8f0f-f14f8de498f4
dc.identifier.otherdspace: 2299/1626
dc.identifier.urihttp://hdl.handle.net/2299/1626
dc.description.abstractThis paper addresses the performance of various statistical data fusion techniques for combining the complementary score information in speaker verification. The complementary verification scores are based on the static and delta cepstral features. Both LPCC (Linear prediction-based cepstral coefficients) and MFCC (mel-frequency cepstral coefficients) are considered in the study. The experiments conducted using a GMM-based speaker verification system, provides valuable information on the relative effectiveness of different fusion methods applied at the score level. It is also demonstrated that a higher speaker discrimination capability can be achieved by applying the fusion at the score level rather than at the feature level.en
dc.language.isoeng
dc.publisherOffice for Official Publications of the European Communities
dc.relation.ispartofProcs of the 3rd COST 275 Workshop on Biometrics on the Internet
dc.rightsOpen
dc.titleFusion of cross stream information in speaker verificationen
dc.contributor.institutionSchool of Engineering and Technology
dc.relation.schoolSchool of Engineering and Technology
dcterms.dateAccepted2005
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue
herts.rights.accesstypeOpen


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