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	CASA Based Speech Separation for Robust Speech Recognition
	Han Runqiang ; Zhao Pei ; Gao Qin ; Zhang Zhiping ; Wu Hao ; Wu Xihong
	2006
关键词	speech separation CASA speaker recognition pitch tracking units grouping reconstruction
英文摘要	This paper introduces a speech separation system as a front-end processing step for automatic speech recognition (ASR). It employs computational auditory scene analysis (CASA) to separate the target speech from the interference speech. Specifically, the mixed speech is preprocessed based on auditory peripheral model. Then a pitch tracking is conducted and the dominant pitch is used as a main cue to find the target speech. Next, the time frequency (TF) units are merged into many segments. These segments are then combined into streams via CASA initial grouping. A regrouping strategy is employed to refine these streams via amplitude modulate (AM) cues, which are finally organized by the speaker recognition techniques into corresponding speakers. Finally, the output streams are reconstructed to compensate the missing data in the abovementioned processing steps by a cluster based feature reconstruction. Experimental results of ASR show that at low TMR (<-6dB) the proposed method offers significantly higher recognition accuracy.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000269965900020&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Computer Science, Artificial Intelligence; Computer Science, Interdisciplinary Applications; CPCI-S(ISTP); 0
语种	英语
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/293552]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Han Runqiang,Zhao Pei,Gao Qin,et al. CASA Based Speech Separation for Robust Speech Recognition. 2006-01-01.

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