Bayesian Confidence Scoring and Adaptation Techniques for Speech Recognition(Multimedia Systems for Communications)
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概要
- 論文の詳細を見る
Bayesian combining of confidence measures is proposed for speech recognition. Bayesian combining is achieved by the estimation of joint pdf of confidence feature vector in correct and incorrect hypothesis classes. In addition, the adaptation of a confidence score using the pdf is presented. The proposed methods reduced the classification error rate by 18% from the conventional single feature based confidence scoring method in isolated word Out-of-Vocabulary rejection test.
- 社団法人電子情報通信学会の論文
- 2005-04-01
著者
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Kim Tae
Department Of Electronics And Computer Engineering Korea University
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Kim Tae
Department Of Anesthesia And Pain Medicine School Of Medicine Pusan National University
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Ko Hanseok
Department Of Electronics And Computer Engineering Korea University
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Kim Tae
Department of Advanced Materials Engineering, Sungkyunkwan University, Suwon, Gyeonggi 440-746, Republic Korea
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