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DC poleHodnotaJazyk
dc.contributor.authorMachlica, Lukáš
dc.contributor.authorZají­c, Zbyněk
dc.date.accessioned2015-12-17T08:46:19Z-
dc.date.available2015-12-17T08:46:19Z-
dc.date.issued2012
dc.identifier.citationMACHLICA, Lukáš; ZAJÍC, Zbyněk. Analysis of the influence of speech corpora in the PLDA verification in the task of speaker recognition. In: Text, speech and dialogue. Berlin: Springer, 2012, p. 464-471. (Lectures notes in computer science; 7499). ISBN 978-3-642-32789-6.en
dc.identifier.isbn978-3-642-32789-6
dc.identifier.urihttp://www.kky.zcu.cz/cs/publications/LukasMachlica_2012_Analysisofthe
dc.identifier.urihttp://hdl.handle.net/11025/17040
dc.format8 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherSpringeren
dc.rights© Lukáš Machlica - Zbyněk Zajíccs
dc.subjectPLDAcs
dc.subjectlatentní prostorcs
dc.subjectfůzecs
dc.subjectsupervektorcs
dc.subjectFAcs
dc.subjecti-vektorcs
dc.titleAnalysis of the influence of speech corpora in the PLDA verification in the task of speaker recognitionen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedIn the paper recent methods used in the task of speaker recognition are presented. At first, the extraction of so called i-vectors from GMM based supervectors is discussed. These i-vectors are of low dimension and lie in a subspace denoted as Total Variability Space (TVS). The focus of the paper is put on Probabilistic Linear Discriminant Analysis (PLDA), which is used as a generative model in the TVS. The influence of development data is analyzed utilizing distinct speech corpora. It is shown that it is preferable to cluster available speech corpora to classes, train one PLDA model for each class and fuse the results at the end. Experiments are presented on NIST Speaker Recognition Evaluation (SRE) 2008 and NIST SRE 2010.en
dc.subject.translatedPLDAen
dc.subject.translatedlatent spaceen
dc.subject.translatedfusionen
dc.subject.translatedsupervectoren
dc.subject.translatedFAen
dc.subject.translatedi-vectoren
dc.identifier.doi10.1007/978-3-642-32790-2_56
dc.type.statusPeer-revieweden
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Články / Articles (NTIS)

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