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The Use of Meta-HMM in Multistream HMM Training for Automatic Speech Recognition

Wellekens, Christian ; Kangasharju, Jussi ; Milesi, Cedric (1998)
The Use of Meta-HMM in Multistream HMM Training for Automatic Speech Recognition.
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Among the different attempts to improve recognition scores and robustness to noise, the recognition of parallel streams of data each one representing partial information on the test signal and the fusion of the decisions have received a great deal of interest. The problem of training such models taking recombination constraints at the level of speech-subunits has not yet been rigorously addressed. This paper shows how equivalence with an extended meta-HMM solves the problem and how reestimation formulas have to be applied to guarantee equivalence between the multistream model and the meta-HMM.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 1998
Autor(en): Wellekens, Christian ; Kangasharju, Jussi ; Milesi, Cedric
Art des Eintrags: Bibliographie
Titel: The Use of Meta-HMM in Multistream HMM Training for Automatic Speech Recognition
Sprache: Deutsch
Publikationsjahr: 1998
Buchtitel: Proceedings of the 5th International Conference on Spoken Language Processing (ICSLP)
Kurzbeschreibung (Abstract):

Among the different attempts to improve recognition scores and robustness to noise, the recognition of parallel streams of data each one representing partial information on the test signal and the fusion of the decisions have received a great deal of interest. The problem of training such models taking recombination constraints at the level of speech-subunits has not yet been rigorously addressed. This paper shows how equivalence with an extended meta-HMM solves the problem and how reestimation formulas have to be applied to guarantee equivalence between the multistream model and the meta-HMM.

ID-Nummer: tk212
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik > Telekooperation
20 Fachbereich Informatik
Hinterlegungsdatum: 31 Dez 2016 12:59
Letzte Änderung: 15 Mai 2018 12:02
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