Research Article
Adaptive Weiner Filter for Speech Enhancement under Various Noisy Conditions
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 170 - Issue 7 |
| Published: Jul 2017 |
| Authors: Akash A. Salmuthe, Rajesh K. Agrawal |
10.5120/ijca2017914912
|
Akash A. Salmuthe, Rajesh K. Agrawal . Adaptive Weiner Filter for Speech Enhancement under Various Noisy Conditions. International Journal of Computer Applications. 170, 7 (Jul 2017), 9-11. DOI=10.5120/ijca2017914912
@article{ 10.5120/ijca2017914912,
author = { Akash A. Salmuthe,Rajesh K. Agrawal },
title = { Adaptive Weiner Filter for Speech Enhancement under Various Noisy Conditions },
journal = { International Journal of Computer Applications },
year = { 2017 },
volume = { 170 },
number = { 7 },
pages = { 9-11 },
doi = { 10.5120/ijca2017914912 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2017
%A Akash A. Salmuthe
%A Rajesh K. Agrawal
%T Adaptive Weiner Filter for Speech Enhancement under Various Noisy Conditions%T
%J International Journal of Computer Applications
%V 170
%N 7
%P 9-11
%R 10.5120/ijca2017914912
%I Foundation of Computer Science (FCS), NY, USA
Abstract
The performance of a noisy speech enhancement algorithm depends on the estimation of the priori signal-to-noise ratio (SNR). The most commonly used approach to estimate the priori SNR parameter uses Decision-Directed (DD), Two Step Noise Reduction (TSNR) and Harmonic Regeneration Noise Reduction (HRNR) method. Two-step noise reduction (TSNR) method eliminate this problem decision-directed method. Common short-time noise reduction techniques introduce harmonic distortion in enhanced speech because of the non-reliability of estimators for small signal to-noise ratios. A simple but effective harmonic regeneration method called Harmonic Regeneration Noise Reduction (HRNR) is used to overcome this problem.
References
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- The University of Texas at Dallas http://ecs.utdallas.edu/
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