Response Time Reduction of Speech Recognizers Using Single Gaussians(Speech and Hearing)
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概要
- 論文の詳細を見る
In this paper, we propose a useful algorithm that can be applied to reduce the response time of speech recognizers based on HMM's. In our algorithm, to reduce the response time, promising HMM states are selected by single Gaussians. In speech recognition, HMM state likelihoods are evaluated by the corresponding single Gaussians first, and then likelihoods by original full Gaussians are computed and replaced only for the HMM states having relatively large likelihoods. By doing so, we can reduce the pattern-matching time for speech recognition significantly without any noticeable loss of the recognition rate. In addition, we cluster the single Gaussians into groups by measuring the distance between Gaussians. Therefore, we can reduce the extra memory much more. In our 10,000 word Korean POI (point-of-interest) recognition task, our proposed algorithm shows 35.57% reduction of the response time in comparison with that of the baseline system at the cost of 10% degradation of the WER.
- 社団法人電子情報通信学会の論文
- 2007-05-01
著者
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Hahn Minsoo
Faculty Of Information And Communications University (icu)
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JEONG Sangbae
Information and Commun. Univ.
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Kim Hoirin
Korea Advanced Inst. Sci. And Technol. Daejeon Kor
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Kim Hoirin
School Of Engineering At Information And Communications University
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Jeong Sangbae
Gyeongsang National Univ. Jinju Kor
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JEONG Sangbae
Faculty of Information and Communications University (ICU)
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KIM Hoirin
Faculty of Information and Communications University (ICU)
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