DocumentCode :
1404056
Title :
A parametric formulation of the generalized spectral subtraction method
Author :
Sim, Boh Lim ; Tong, Yit Chow ; Chang, Joseph S. ; Tan, Chin Tuan
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Inst., Singapore
Volume :
6
Issue :
4
fYear :
1998
fDate :
7/1/1998 12:00:00 AM
Firstpage :
328
Lastpage :
337
Abstract :
In this paper, two short-time spectral amplitude estimators of the speech signal are derived based on a parametric formulation of the original generalized spectral subtraction method. The objective is to improve the noise suppression performance of the original method while maintaining its computational simplicity. The proposed parametric formulation describes the original method and several of its modifications. Based on the formulation, the speech spectral amplitude estimator is derived and optimized by minimizing the mean-square error (MSE) of the speech spectrum. With a constraint imposed on the parameters inherent in the formulation, a second estimator is also derived and optimized. The two estimators are different from those derived in most modified spectral subtraction methods, which are predominantly nonstatistical. When tested under stationary white Gaussian noise and semistationary Jeep noise, they showed improved noise suppression results
Keywords :
Gaussian noise; acoustic noise; amplitude estimation; interference suppression; least mean squares methods; spectral analysis; speech processing; white noise; computational simplicity; generalized spectral subtraction method; least mean-square error; noise suppression; noise suppression performance; parametric formulation; semistationary Jeep noise; short-time spectral amplitude estimators; speech signal; speech spectral amplitude estimator; speech spectrum; stationary white Gaussian noise; Acoustic noise; Amplitude estimation; Automatic speech recognition; Constraint optimization; Gaussian noise; Noise level; Noise reduction; Speech enhancement; Speech processing; Testing;
fLanguage :
English
Journal_Title :
Speech and Audio Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1063-6676
Type :
jour
DOI :
10.1109/89.701361
Filename :
701361
Link To Document :
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