Publikace
Detail publikace
Citace
p. 52-59, Springer, 2013. : A Direct Criterion Minimization based fMLLR via Gradient Descend . Text, Speech, and Dialogue, Lecture Notes in Computer Science, vol. 8082,
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Abstrakt
Adaptation 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 HMM state. It estimates the transformation to optimize the ML criterion of HMM directly using gradient descent algorithm.
Abstrakt v češtině
Adaptation 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 HMM state. It estimates the transformation to optimize the ML criterion of HMM directly using gradient descent algorithm.
Detail publikace
Název: | A Direct Criterion Minimization based fMLLR via Gradient Descend |
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Autor: | Jan Vaněk ; Zbyněk Zajíc |
Název - česky: | A Direct Criterion Minimization based fMLLR via Gradient Descend |
Jazyk publikace: | anglicky |
Datum vydání: | 1.9.2013 |
Rok vydání: | 2013 |
Typ publikace: | Stať ve sborníku |
Název knihy: | Text, Speech, and Dialogue |
Svazek: | Lecture Notes in Computer Science |
Číslo vydání: | 8082 |
Strana: | 52 - 59 |
DOI: | 10.1007/978-3-642-40585-3_8 |
ISBN: | 978-3-642-40584-6 |
Nakladatel: | Springer |
Klíčová slova
ASR, adaptation, fMLLR, gradient descend, Hessian matrix
Klíčová slova v češtině
ASR, adaptation, fMLLR, gradient descend, Hessian matrix
BibTeX
@INPROCEEDINGS{JanVanek_2013_ADirectCriterion, author = {Jan Van\v{e}k and Zbyn\v{e}k Zaj\'{i}c}, title = {A Direct Criterion Minimization based fMLLR via Gradient Descend}, year = {2013}, publisher = {Springer}, volume = {8082}, pages = {52-59}, booktitle = {Text, Speech, and Dialogue}, series = {Lecture Notes in Computer Science}, ISBN = {978-3-642-40584-6}, doi = {10.1007/978-3-642-40585-3_8}, url = {http://www.kky.zcu.cz/en/publications/JanVanek_2013_ADirectCriterion}, }