BionicWavelet Based Denoising Using Source Separation

Authors

  • Mourad Talbi Faculty of Sciences of Tunis, Laboratory of Signal Processing, University Campus, 2092 El Manar II, Tunis, Tunisia
  • Anis Ben Aicha Université de Carthage, Ecole Supérieure des Communications Laboratoire de recherche COSIM Route de Raoued 3.5 Km, Cité El Ghazala, Ariana, 2083, Tunisie, Tél. : +216 71 857 000 - Fax : +216 71 856 829
  • Lotfi Salhi Faculty of Sciences of Tunis, Laboratory of Signal Processing, University Campus, 2092 El Manar II, Tunis, Tunisia
  • Adnene Cherif Faculty of Sciences of Tunis, Laboratory of Signal Processing, University Campus, 2092 El Manar II, Tunis, Tunisia

Keywords:

Bionic wavelet transform, Blinde Source Separation, entropy, speech enhancement

Abstract

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.

Author Biography

Mourad Talbi, Faculty of Sciences of Tunis, Laboratory of Signal Processing, University Campus, 2092 El Manar II, Tunis, Tunisia

Department of Mathematics and Computer Science

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Published

2014-09-18

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