DocumentCode
1742183
Title
Stochastic modelling: From pattern classification to speech recognition and translation
Author
Ney, Hermann
Author_Institution
Lehrstuhl fur Inf. VI, Tech. Hochschule Aachen, Germany
Volume
3
fYear
2000
fDate
2000
Firstpage
21
Abstract
This paper gives an overview of the stochastic modelling approach in automatic speech recognition and language translation. Starting from the Bayes decision rule for minimum error rate, we present the stochastic modelling approach to speech recognition and analyze its characteristic properties. We discuss the advantages of stochastic modelling and extend it to the translation of written language.
Keywords
Bayes methods; error analysis; language translation; pattern classification; speech recognition; stochastic systems; Bayes decision rule; language translation; minimum error rate; pattern classification; speech recognition; speech translation; stochastic modelling; stochastic modelling approach; written language translation; Automatic speech recognition; Computer science; Error analysis; Loudspeakers; Natural languages; Pattern classification; Speech processing; Speech recognition; Statistics; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2000. Proceedings. 15th International Conference on
ISSN
1051-4651
Print_ISBN
0-7695-0750-6
Type
conf
DOI
10.1109/ICPR.2000.903478
Filename
903478
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