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Wiener filter for Noise Reduction and speech enhancement

Version 2.1.0.1 (214 KB) by Pascal Scalart
Wiener Noise Suppressor based on Decision-Directed method with TSNR and HRNR algorithms.
4.1
(19)

13.4K Downloads

Updated 23 Oct 2020

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The two-step noise reduction (TSNR) technique removes the annoying reverberation effect while maintaining the benefits of the decision-directed approach. However, classic short-time noise reduction techniques, including TSNR, introduce harmonic distortion in the enhanced speech. To overcome this problem, a method called harmonic regeneration noise reduction (HRNR) is implemented in order to refine the a priori SNR used to compute a spectral gain able to preserve the speech harmonics as proposed by Plapous et al.
("Improved Signal-to-Noise Ratio Estimation for Speech Enhancement", IEEE Transactions on ASLP, Vol. 14, Issue 6, pp. 2098 - 2108, Nov. 2006).

%% example with the noisy speech file car.wav
>> [x,fs] = audioread('car.wav');
>> [out,~] = WienerNoiseReduction(x,fs,10000) % first 10000 samples are noise samples (without speech)
>> soundsc(out(1:122000),fs)

Cite As

Pascal Scalart (2023). Wiener filter for Noise Reduction and speech enhancement (https://www.mathworks.com/matlabcentral/fileexchange/24462-wiener-filter-for-noise-reduction-and-speech-enhancement), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2008a
Compatible with any release
Platform Compatibility
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Version Published Release Notes
2.1.0.1

An image as been added
2.1.0.0

1) the error that was mentionned by several users has been fixed (data was changed to ns)
2) a minimum value is introduced for the filter gain (in lines 107 and 135)
3) an amplitude normalization factor is introduced (in lines 147 and 148)
1.1.0.0

new tags have been added.
1.0.0.0