TY - JOUR
T1 - Bayesian fusion of confidence measures for speech recognition
AU - Kim, Tae Yoon
AU - Ko, Hanseok
N1 - Funding Information:
Manuscript received April 4, 2005; revised June 27, 2005. This work was supported under Grant C1012-0403-0001 from an International Joint Research Project of IITA. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Frederic Bimbot. The authors are with the Department of Electrical and Computer Engineering, Korea University, Seoul 136-701, Korea. Digital Object Identifier 10.1109/LSP.2005.859494
Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2005/12
Y1 - 2005/12
N2 - The application of Bayesian fusion of confidence measures to speech recognition is proposed. Feature level, decision level, and hybrid fusion are considered under the Bayesian framework. The use of speaker-adapted feature-level Bayesian fusion reduced the error rate by 19.4% as compared to the conventional single feature-based confidence scoring in an isolated word out-of-vocabulary rejection test. The decision-level Bayesian fusion also showed better performance than the majority rule. Finally, hybrid Bayesian fusion, which can combine both confidence measure features and local decisions, achieved the best performance.
AB - The application of Bayesian fusion of confidence measures to speech recognition is proposed. Feature level, decision level, and hybrid fusion are considered under the Bayesian framework. The use of speaker-adapted feature-level Bayesian fusion reduced the error rate by 19.4% as compared to the conventional single feature-based confidence scoring in an isolated word out-of-vocabulary rejection test. The decision-level Bayesian fusion also showed better performance than the majority rule. Finally, hybrid Bayesian fusion, which can combine both confidence measure features and local decisions, achieved the best performance.
KW - Adaptive confidence scoring
KW - Bayesian fusion
KW - Confidence measure (CM)
KW - Speech recognition
UR - http://www.scopus.com/inward/record.url?scp=29144490102&partnerID=8YFLogxK
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U2 - 10.1109/LSP.2005.859494
DO - 10.1109/LSP.2005.859494
M3 - Article
AN - SCOPUS:29144490102
VL - 12
SP - 871
EP - 874
JO - IEEE Signal Processing Letters
JF - IEEE Signal Processing Letters
SN - 1070-9908
IS - 12
ER -