DocumentCode
1188070
Title
Bayes-based confidence measure in speech recognition
Author
Yoma, Néstor Becerra ; Carrasco, Jorge ; Molina, Carlos
Author_Institution
Dept. of Electr. Eng., Univ. de Chile Santiago, Chile
Volume
12
Issue
11
fYear
2005
Firstpage
745
Lastpage
748
Abstract
In this letter, Bayes-based confidence measure (BBCM) in speech recognition is proposed. BBCM is applicable to any standard word feature and makes use of information about the speech recognition engine performance. In contrast to ordinary confidence measures, BBCM is a probability, which is interesting itself from the practical and theoretical point of view. If applied with word density confidence measure (WDCM), BBCM dramatically improves the discrimination ability of the false acceptance curve when compared to WDCM itself.
Keywords
Bayes methods; feature extraction; speech recognition; BBCM; Bayes-based confidence measure; WDCM; dialogue system; false acceptance curve; speech recognition; standard word feature; word density confidence measure; Acoustic measurements; Automatic speech recognition; Decoding; Density measurement; Engines; Humans; Natural languages; Speech recognition; Telephony; Viterbi algorithm; Bayes theorem; confidence measure; dialogue systems; speech recognition;
fLanguage
English
Journal_Title
Signal Processing Letters, IEEE
Publisher
ieee
ISSN
1070-9908
Type
jour
DOI
10.1109/LSP.2005.856888
Filename
1518891
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