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
Link To Document :
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