Impostor detection in speaker recognition using confusion-based confidence measures

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dc.contributor.authorKim, Kwang-Kiko
dc.contributor.authorKim, Hoi-Rinko
dc.contributor.authorHahn, Min-Sooko
dc.date.accessioned2011-03-29T05:51:28Z-
dc.date.available2011-03-29T05:51:28Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2006-12-
dc.identifier.citationETRI JOURNAL, v.28, no.6, pp.811 - 814-
dc.identifier.issn1225-6463-
dc.identifier.urihttp://hdl.handle.net/10203/23068-
dc.description.abstractIn this letter we introduce confusion-based confidence measures for detecting an impostor in speaker recognition, which does not require an alternative hypothesis. Most traditional speaker verification methods are based on a hypothesis test, and their performance depends on the robustness of an alternative hypothesis. Compared with the conventional Gaussian mixture model-universal background model (GMM-UBM)) scheme, our confusion-based measures show better performance in noise-corrupted speech. The additional computational requirements for our methods are negligible when used to detect or reject impostors.-
dc.languageEnglish-
dc.language.isoen_USen
dc.publisherELECTRONICS TELECOMMUNICATIONS RESEARCH INST-
dc.subjectMODELS-
dc.subjectIDENTIFICATION-
dc.titleImpostor detection in speaker recognition using confusion-based confidence measures-
dc.typeArticle-
dc.identifier.wosid000242809400017-
dc.identifier.scopusid2-s2.0-33845401776-
dc.type.rimsART-
dc.citation.volume28-
dc.citation.issue6-
dc.citation.beginningpage811-
dc.citation.endingpage814-
dc.citation.publicationnameETRI JOURNAL-
dc.contributor.localauthorKim, Hoi-Rin-
dc.contributor.localauthorHahn, Min-Soo-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorspeaker recognition-
dc.subject.keywordAuthorspeaker verification-
dc.subject.keywordAuthoropen-set speaker identification-
dc.subject.keywordAuthorconfidence measure-
dc.subject.keywordPlusMODELS-
dc.subject.keywordPlusIDENTIFICATION-

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