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连续语音的三音子DDBHMM识别方法
引用本文:游展,肖熙,王作英.连续语音的三音子DDBHMM识别方法[J].清华大学学报(自然科学版),2009(4).
作者姓名:游展  肖熙  王作英
作者单位:清华大学电子工程系;
基金项目:国家自然科学基金资助项目(60402029)
摘    要:针对目前连续语音识别中广泛使用的齐次HMM(hidden Markov model)模型识别精度低的现状,该文提出了三音子DDBHMM(duration distribution based HMM)识别方法。根据汉语的特点,设计了适用于连续语音识别的三音子。描述了识别中使用的MLSS(most likely statesequence)准则。设计了识别网络并阐明了用于三音子识别的帧同步识别算法。将三音子DDBHMM识别方法与三音子齐次HMM识别方法和双音子DDBHMM识别方法进行了实验对比,结果表明:采用三音子DDBHMM可以使得识别错误率分别下降0.95%和2.29%。说明该方法能够显著地改进连续语音识别性能。

关 键 词:语音识别  段长  DDBHMM  三音子  

Continuous speech recognition based on the triphone DDBHMM
YOU Zhan,XIAO Xi,WANG Zuoying.Continuous speech recognition based on the triphone DDBHMM[J].Journal of Tsinghua University(Science and Technology),2009(4).
Authors:YOU Zhan  XIAO Xi  WANG Zuoying
Institution:Department of Electronic Engineering;Tsinghua University;Beijing 100084;China
Abstract:The HMM(hidden Markov model) is widely used in continuous speech recognition,but the recognition rate can still be improved.This paper presents a triphone DDBHMM(duration distribution-based HMM) recognition method to improve the recognition performance.The triphone used for the continuous speech recognition was designed based on the Chinese language characteristics.MLSS(most likely state sequence) rules are described with a recognition network designed based on the frame-synchronous recognition algorithm.Th...
Keywords:speech recognition  duration  DDBHMM  triphone  
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