Title: | Refinement approach for adaptation based on combination of MAP and fMLLR |
Other Titles: | Zlepšený přístup k adaptaci založené na kombinaci MAP a fMLLR |
Authors: | Zajíc, Zbyněk Machlica, Lukáš Müller, Luděk |
Citation: | ZAJÍC, 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. |
Issue Date: | 2009 |
Publisher: | Springer |
Document type: | článek article |
URI: | http://www.kky.zcu.cz/cs/publications/ZbynekZajic_2009_RefinementApproach http://hdl.handle.net/11025/16954 |
ISBN: | 978-3-642-04207-2 |
Keywords: | adaptace;fMLLR;MAP |
Keywords in different language: | adaptation;fMLLR;MAP |
Abstract in different language: | This 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. |
Rights: | © Zbyněk Zajíc - Lukáš Machlica - Luděk Müller |
Vyskytuje se v kolekcích: | Články / Articles (KKY) Články / Articles (NTIS) |
Soubory připojené k záznamu:
Soubor | Popis | Velikost | Formát | |
---|---|---|---|---|
ZbynekZajic_2009_RefinementApproach.pdf | Plný text | 191,73 kB | Adobe PDF | View/Open |
Please use this identifier to cite or link to this item:
http://hdl.handle.net/11025/16954
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.