Monaural speech separation based on MAXVQ and CASA for robust speech recognition
Li, Peng; Guan, Yong; Wang, Shijin; Xu, Bo; Liu, Wenju
刊名COMPUTER SPEECH AND LANGUAGE
2010
卷号24期号:1页码:30-44
关键词Monaural Speech Separation Computational Auditory Scene Analysis (Casa) Factorial-max Vector Quantization (Maxvq) Automatic Speech Recognition (Asr)
文献子类Article
英文摘要Robustness is one of the most important topics for automatic speech recognition (ASR) in practical applications. Monaural speech separation based on computational auditory scene analysis (CASA) offers a solution to this problem. In this paper, a novel system is presented to separate the monaural speech of two talkers. Gaussian mixture models (GMMs) and vector quantizers (VQs) are used to learn the grouping cues on isolated clean data for each speaker. Given an utterance, speaker identification is firstly performed to identify the two speakers presented in the utterance, then the factorial-max vector quantization model (MAXVQ) is used to infer the mask signals and finally the utterance of the target speaker is resynthesized in the CASA framework. Recognition results on the 2006 speech separation challenge corpus prove that this proposed system can improve the robustness of ASR significantly. (C) 2008 Elsevier Ltd. All rights reserved.
WOS关键词AUDITORY SCENE ANALYSIS ; MAXIMUM-LIKELIHOOD-ESTIMATION ; HIDDEN MARKOV-MODELS ; BIAS REMOVAL ; NOISE ; ADAPTATION
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000270630700003
内容类型期刊论文
源URL[http://ir.ia.ac.cn/handle/173211/40959]  
专题数字内容技术与服务研究中心_听觉模型与认知计算
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GB/T 7714
Li, Peng,Guan, Yong,Wang, Shijin,et al. Monaural speech separation based on MAXVQ and CASA for robust speech recognition[J]. COMPUTER SPEECH AND LANGUAGE,2010,24(1):30-44.
APA Li, Peng,Guan, Yong,Wang, Shijin,Xu, Bo,&Liu, Wenju.(2010).Monaural speech separation based on MAXVQ and CASA for robust speech recognition.COMPUTER SPEECH AND LANGUAGE,24(1),30-44.
MLA Li, Peng,et al."Monaural speech separation based on MAXVQ and CASA for robust speech recognition".COMPUTER SPEECH AND LANGUAGE 24.1(2010):30-44.
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