Reduction of Broadband Noise In Speech Signals by Multilinear Subspace Analysis

被引：0
|
作者：
Sato, Yusuke [1 ]
Hoya, Tetsuya [1 ,2 ]
Bakardjian, Hovagim [2 ]
Cichocki, Andrzej [2 ]
机构：
[1] Nihon Univ, Coll Sci & Technol, Dept Math, Chiyoda Ku, 1-8-14 Kanda Surugadai, Tokyo 1018308, Japan
[2] BSI RIKEN, Lab Adv Brain Signal Proc, Wakoh City, Saitama 3510198, Japan
来源：
11TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2010 (INTERSPEECH 2010), VOLS 1-2 | 2010年
关键词：
speech enhancement; broadband noise reduction; multilinear subspace analysis; ENHANCEMENT;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A new noise reduction method for speech signals is proposed in this paper. The method is based upon the N-mode singular value decomposition algorithm, which exploits the multilinear subspace analysis of given speech data. Simulation results using both synthetically generated and real broadband noise components show that the enhancement quality obtained by the multilinear subspace analysis method in terms of both segmental gain and cepstral distance, as well as informal listening tests, is superior to that by a conventional nonlinear spectral subtraction method and the previously proposed approach based upon sliding subspace projection.
引用
收藏
页码：965 / +
页数：3
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