BionicWavelet Based Denoising Using Source Separation

We consider the problem of speech denoising using source separation. In this study we have proposed a hybrid technique that consists in applying in the first step, the Bionic Wavelet Transform (BWT) to two different mixtures of the same speech signal with noise. This speech signal is corrupted by a...

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Bibliographic Details
Published in:International journal of computers, communications & control communications & control, 2014-09, Vol.7 (3), p.574
Main Authors: Talbi, Mourad, Aicha, Anis Ben, Salhi, Lotfi, Cherif, Adnene
Format: Article
Language:English
Subjects:
Bionics
Entropy
Noise
Noise reduction
Separation
Signal to noise ratio
Speech
Wavelet transforms
White noise
Yard waste
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Summary:We consider the problem of speech denoising using source separation. In this study we have proposed a hybrid technique that consists in applying in the first step, the Bionic Wavelet Transform (BWT) to two different mixtures of the same speech signal with noise. This speech signal is corrupted by a Gaussian white noise with two different values of the Signal to Noise Ratio (SNR) in order to obtain those two mixtures. The second step consists in computing the entropy of each bionic wavelet coefficient and finds the two subbands having the minimal entropy. Those two subbands are used to estimate the separation matrix of the speech signal from noise by using the source separation. Our proposed technique is evaluated by comparing it to the denoising technique based on source separation in time domain.
ISSN:1841-9836
1841-9844
DOI:10.15837/ijccc.2012.3.1397