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Noisy Speech Enhancement Using Soft Thresholding on Selected Intrinsic Mode Functions
Hadhami Issaoui , Aïcha Bouzid, Noureddine Ellouze
Pages - 93 - 100     |    Revised - 01-07-2011     |    Published - 05-08-2011
Volume - 5   Issue - 3    |    Publication Date - July / August 2011  Table of Contents
Empirical Mode Decomposition, Speech Enhancement, Soft thresholding, Mode-Selection
In this paper, a new speech enhancement method is introduced. It is essentially based on the Empirical Mode Decomposition technique (EMD) and a soft thresholding approach applied on selected modes. The proposed method is a fully data driven approach. First the noisy speech signal is decomposed adaptively into intrinsic oscillatory components called Intrinsic Mode Functions (IMFs) by using a time decomposition called sifting process. Second, selected IMFs are soft thresholded and added to the remaining IMFs with the residue to reconstitute the enhanced speech signal. The proposed approach is evaluated using speech signals from NOISEUS database corrupted with additive white Gaussian noise. Our algorithm is compared to other state of the art algorithms.
CITED BY (3)  
1 Hadhami, I., & Aicha, B. (2014). Speech Signal Enhancement Using Empirical Mode Decomposition and Adaptive Method Based on the Signal for Noise Ratio Objective Evaluation. International Review on Computers and Software (IRECOS), 9(8), 1461-1467.
2 Hadhami, I., & Bouzid, A. (2013). Speech Denoising Based on Empirical Mode Decomposition and Improved Thresholding. In Advances in Nonlinear Speech Processing (pp. 200-207). Springer Berlin Heidelberg.
3 Issaoui, H., & Bouzid, A. Speech Signal Enhancement using Empirical Mode Decomposition and Adaptive Method based on the Signal for Noise Ratio Objective Evaluation.
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Mr. Hadhami Issaoui
Institut supérieur des étude technologique de Gafsa - Tunisia
Professor Aïcha Bouzid
Electrical Engineering Department - Tunisia
Professor Noureddine Ellouze
Electrical Engineering Department - Tunisia