A wavelet Kalman filter with perceptual masking for speech enhancement in colored noise

被引：0
|
作者：
Ma, N [1 ]
Bouchard, M [1 ]
Goubran, RA [1 ]
机构：
[1] Univ Ottawa, Sch Informat Technol & Engn, Ottawa, ON K1N 6N5, Canada
来源：
2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1-5: SPEECH PROCESSING | 2005年
关键词：
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 wavelet Kalman filter combined with masking properties of human auditory systems is proposed for enhancing speech degraded by colored noise. A wavelet domain speech state-space model is first constructed, with a corresponding Kalman filter. A post-filter considering both time and frequency masking properties is then applied. From the calculated masking threshold, the noisy speech spectrum is further enhanced. Simulation results show that the proposed approach has the best performance compared with either classic or recently introduced methods, evaluated using ITU-T P.862 PESQ scores. The proposed approach also has a reduced complexity compared to a time-domain implementation of the Kalman filter with a perceptual post-filter.
引用
收藏
页码：149 / 152
页数：4
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