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dc.contributor.authorZají­c, Zbyněk
dc.contributor.authorMachlica, Lukáš
dc.contributor.authorMüller, Luděk
dc.date.accessioned2015-12-10T12:32:35Z-
dc.date.available2015-12-10T12:32:35Z-
dc.date.issued2009
dc.identifier.citationZAJÍC, Zbyněk; MACHLICA, Lukᚡ; MÜLLER, Luděk. Refinement approach for adaptation based on combination of MAP and fMLLR. In: Text, speech and dialogue. Berlin: Springer, 2009, p. 274-281. (Lecture notes in computer science; 5729). ISBN 978-3-642-04207-2.en
dc.identifier.isbn978-3-642-04207-2
dc.identifier.urihttp://www.kky.zcu.cz/cs/publications/ZbynekZajic_2009_RefinementApproach
dc.identifier.urihttp://hdl.handle.net/11025/16954
dc.format8 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherSpringeren
dc.relation.ispartofseriesLecture notes in computer science; 5729en
dc.rights© Zbyněk Zají­c - Lukáš Machlica - Luděk Müllercs
dc.subjectadaptacecs
dc.subjectfMLLRcs
dc.subjectMAPcs
dc.titleRefinement approach for adaptation based on combination of MAP and fMLLRen
dc.title.alternativeZlepšený přístup k adaptaci založené na kombinaci MAP a fMLLRcs
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedThis paper deals with a combination of basic adaptation techniques of Hidden Markov Model used in the speech recognition. The adaptation methods approach the data only through their statistics, which have to be accumulated before the adaptation process. When performing two adaptations subsequently, the data statistics have to be accumulated twice in each of the adaptation passes. However, when the adaptation methods are chosen with care, the data statistics may be accumulated only once, as proposed in this paper. This significantly reduces the time consumption and avoids the need to store all the adaptation data. Combination of Maximum A-Posteriori Probability and feature Maximum Likelihood Linear Regression adaptation is considered. Motivation for such an approach could be the on-line adaptation, where the time consumption is of big importance.en
dc.subject.translatedadaptationen
dc.subject.translatedfMLLRen
dc.subject.translatedMAPen
dc.type.statusPeer-revieweden
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