Full metadata record
DC poleHodnotaJazyk
dc.contributor.authorVaněk, Jan
dc.contributor.authorZajíc, Zbyněk
dc.date.accessioned2016-01-07T12:18:48Z
dc.date.available2016-01-07T12:18:48Z
dc.date.issued2013
dc.identifier.citationVANĚK, Jan; ZAJÍC, Zbyněk. A direct criterion minimization based fMLLR via gradient descend. In: Text, speech and dialogue. Berlin: Springer, 2013, p. 52-59. (Lectures notes in computer science; 8082). ISBN 978-3-642-40584-6.en
dc.identifier.isbn978-3-642-40584-6
dc.identifier.urihttp://www.kky.zcu.cz/cs/publications/JanVanek_2013_ADirectCriterion
dc.identifier.urihttp://hdl.handle.net/11025/17162
dc.format8 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherSpringeren
dc.relation.ispartofseriesLecture notes in computer science; 8082en
dc.rights© Jan Vaněk - Zbyněk Zajíccs
dc.subjectASRcs
dc.subjectfMLLRcs
dc.subjectadaptacecs
dc.titleA direct criterion minimization based fMLLR via gradient descenden
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedAdaptation techniques are necessary in automatic speech recognizers to improve a recognition accuracy. Linear Transformation methods (MLLR or fMLLR) are the most favorite in the case of limited available data. The fMLLR is the feature-space transformation. This is the advantage with contrast to MLLR that transforms the entire acoustic model. The classical fMLLR estimation involves maximization of the likelihood criterion based on individual Gaussian components statistic.We proposed an approach which takes into account the overall likelihood of a HMMstate. It estimates the transformation to optimize the ML criterion of HMM directly using gradient descent algorithm.en
dc.subject.translatedASRen
dc.subject.translatedfMLLRen
dc.subject.translatedadaptationen
dc.identifier.doi10.1007/978-3-642-40585-3_8
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:Články / Articles (NTIS)

Soubory připojené k záznamu:
Soubor Popis VelikostFormát 
JanVanek_2013_ADirectCriterion.pdfPlný text101,06 kBAdobe PDFZobrazit/otevřít


Použijte tento identifikátor k citaci nebo jako odkaz na tento záznam: http://hdl.handle.net/11025/17162

Všechny záznamy v DSpace jsou chráněny autorskými právy, všechna práva vyhrazena.