DocumentCode :
312124
Title :
H filtering for speech enhancement
Author :
Shen, Xuemin ; Deng, Li ; Tasmin, A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Waterloo Univ., Ont., Canada
Volume :
2
fYear :
1996
fDate :
3-6 Oct 1996
Firstpage :
873
Abstract :
A new approach based on H filtering is presented for speech enhancement. This approach differs from the traditional modified Wiener/Kalman filtering approach in the following two aspects: 1) no a priori knowledge of the noise statistics is required; instead the noise signals are only assumed to have finite energy; 2) the estimation criterion for the filter design is to minimize the worst possible amplification of the estimation error signal in terms of the modeling errors and additive noises. Since most additive noises in speech are not Gaussian, this approach is highly robust and is more appropriate in practical speech enhancement. The global signal-to-noise ratio (SNR), time domain speech representation and listening evaluations are used to verify the performance of the H filtering algorithm. Experimented results show that the filtering performance is better than other speech enhancement approaches in the literature under similar experimental conditions
Keywords :
Kalman filters; Wiener filters; amplification; errors; filtering theory; noise; speech enhancement; time-domain analysis; H filtering; H filtering algorithm performance verification; Kalman filtering; Wiener filtering; additive noise; estimation criterion; estimation error signal; filter design; finite energy noise signals; global signal-to-noise ratio; listening evaluations; modeling errors; speech enhancement; time domain speech representation; Additive noise; Error analysis; Estimation error; Filtering; Kalman filters; Noise robustness; Signal design; Signal to noise ratio; Speech enhancement; Wiener filter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Spoken Language, 1996. ICSLP 96. Proceedings., Fourth International Conference on
Conference_Location :
Philadelphia, PA
Print_ISBN :
0-7803-3555-4
Type :
conf
DOI :
10.1109/ICSLP.1996.607740
Filename :
607740
Link To Document :
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