Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/67645
DC FieldValueLanguage
dc.contributorDepartment of Electronic and Information Engineering-
dc.creatorMak, MW-
dc.date.accessioned2017-07-27T08:33:53Z-
dc.date.available2017-07-27T08:33:53Z-
dc.identifier.isbn978-9-8814-7680-7 (electronic)-
dc.identifier.isbn978-1-4673-9593-9 (print on demand(PoD))-
dc.identifier.urihttp://hdl.handle.net/10397/67645-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.subjectSignal to noise ratioen_US
dc.subjectComputational complexityen_US
dc.subjectAcousticsen_US
dc.subjectComputational modelingen_US
dc.subjectNoise measurementen_US
dc.subjectFeature extractionen_US
dc.subjectAnalytical modelsen_US
dc.titleFast scoring for mixture of PLDA in i-vector/PLDA speaker verificationen_US
dc.typeConference Paperen_US
dc.identifier.spage587-
dc.identifier.epage593-
dc.identifier.doi10.1109/APSIPA.2015.7415337-
dcterms.abstractWith the ubiquitous of mobile phones, users of speaker verification systems will perform authentication anywhere at anytime. As a result, practical speaker verification systems need to deal with utterances of different noise levels. Recently, an SNR-dependent mixture of PLDA model was proposed to deal with such practical situation. However, the scoring function of this model is significantly more complex than the conventional one. This paper proposes a method to reduce the computation burden of this mixture PLDA model. The idea is based on the observation that for most utterances, the posterior probabilities of SNR are very sparse so that it is possible to consider the top Gaussian only during scoring. The method effectively reduces the computational complexity from O(K2D3) to O(D3), where K and D are the number of mixtures and i-vector dimension, respectively. Experimental results based on NIST 2012 SRE suggest that the proposed method can reduce computation time by 60% with very minor degradation in performance.-
dcterms.bibliographicCitation2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA), Hong Kong, China, 16-19 Dec 2015, p.587-593-
dcterms.issued2015-
dc.relation.conferenceAsia-Pacific Signal and Information Processing Association (APSIPA). Summit and Conference-
dc.identifier.rosgroupid2015002471-
dc.description.ros2015-2016 > Academic research: refereed > Refereed conference paper-
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