DocumentCode
614531
Title
Frequency dependent statistical model for the suppression of late reverberations
Author
Jan, Tariqullah ; Wenwu Wang
Author_Institution
Dept. of Electr. Eng., Univ. of Eng. & Technol., Peshawar, Pakistan
fYear
2012
fDate
25-27 Sept. 2012
Firstpage
1
Lastpage
5
Abstract
Suppression of late reverberations is a challenging problem in reverberant speech enhancement. A promising recent approach to this problem is to apply a spectral subtraction mask to the spectrum of the reverberant speech, where the spectral variance of the late reverberations was estimated based on a frequency independent statistical model of the decay rate of the late reverberations. In this paper, we develop a dereverberation algorithm by following a similar process. Instead of using the frequency independent model, however, we estimate the frequency dependent reverberation time and decay rate, and use them for the estimation of the spectral subtraction mask. In order to remove the processing artifacts, the mask is further filtered by a smoothing function, and then applied to reduce the late reverberations from the reverberant speech. The performance of the proposed algorithm, measured by the segmental signal to reverberation ratio (SegSRR) and the signal to distortion ratio (SDR), is evaluated for both simulated and real data. As compared with the related frequency indepenent algorithm, the proposed algorithm offers considerable performance improvement.
Keywords
reverberation; smoothing methods; speech enhancement; statistical analysis; SDR; SegSRR; decay rate; dereverberation algorithm; frequency dependent reverberation time; frequency dependent statistical model; frequency independent statistical model; late reverberations; reverberant speech enhancement; segmental signal to reverberation ratio; signal to distortion ratio; smoothing function; spectral subtraction mask; spectral variance;
fLanguage
English
Publisher
iet
Conference_Titel
Sensor Signal Processing for Defence (SSPD 2012)
Conference_Location
London
Electronic_ISBN
978-1-84919-712-0
Type
conf
DOI
10.1049/ic.2012.0091
Filename
6552159
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