Utterance verification using search confusion rate and its N-best approach

Recently a variety of confidence measures for utterance verfication has been studied to improve speech recognition performance by rejecting out-of-vocabulary inputs. Most of the conventional confidence measures for utterance verification are based primarily on hypothesis testing or an approximated posterior probability, and their performances depend on the robustness of an alternative hypothesis or the prior probability. We introduce a novel confidence measure called a search confusion rate (SCR), which does not require an alternative hypothesis or the approximation of posterior probability. Our confusion-based approach shows better performance in additive noise-corrupted speech as well as in clean speech.
Publisher
ELECTRONICS TELECOMMUNICATIONS RESEARCH INST
Issue Date
2005-08
Language
ENG
Keywords

SPEECH RECOGNITION

Citation

ETRI JOURNAL, v.27, pp.461 - 464

ISSN
1225-6463
DOI
10.4218/etrij.05.0205.0027
URI
http://hdl.handle.net/10203/23062
Appears in Collection
EE-Journal Papers(저널논문)
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