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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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1 A.O. Boudraa and J.C. Cexus, Denoising via empirical mode decomposition, in Proc. IEEE ISCCSP, Marrakech Morocco, 2006.
2 S. F. Boll, Suppression of acoustic noise in speech using spectral subtraction, IEEE Transactions on Acoustics Speech and Signal Processing, ASSP-27 pp. 113-120, 1979
3 A. Sumithra M G , B. Thanuskodi K, C. Anitha M R, Modified Time Adaptive Wavelet Based Approach for Enhancing Speech from Adverse Noisy Environments, DSP Journal, Volume 9, Issue 1, p.p. 33-40, June, 2009
4 D.L. Donoho, De-noising by soft-thresholding, IEEE Trans. on Information Theory,41(3):613627, 1995.
5 D.L. Donoho and I.M. Johnstone, Ideal spatial adaptation via wavelet shrinkage,Biometrica, vol. 81, pp. 425455, 1994.
6 S. Mallat, Une Exploration Des Signaux En Ondelettes, Ellipses, Paris, France, 2000.
7 N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shin, Q. Zheng, N. C. Yen, C. C. Tung,and H. H. Liu, The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, Proc. R. Soc. Lond. A, Math. Phys. Sci., Mar.1998, vol. 454, no. 1971, pp. 903995.
8 E. Derger, Md. K. I. Molla, M. Hirose, N. Minematsu, and Md. K. Hasan, Speech Enhancement using Soft Thresholding with DCT-EMD Based Hybrid algorithm, Proc.EUSIPCO-2007, Poznan, POLAND, 2007, pp. 7579.
9 J.C. Cexus, Analyse des signaux non-stationnaires par Transformation de Huang,Oprateur de Teager-Kaiser, et Transformation de Huang-Teager (THT), Thesis,Universit de Rennes 1, 2005.
10 A. O. Boudraa, and J.C. Cexus, EMD-Based Signal Filtering, IEEE Trans. On Instrumentation and measurement, vol. 56, no. 6, pp. 21962202, December 2007.
11 A.O. Boudraa, J.C. Cexus, and Z. Saidi, EMD-based signal noise reduction, Int. J. Sig.Process., vol. 1, no. 1, pp. 3337, 2004, ISSN: 1304-4494.
12 D. H. Klatt, Prediction of Perceived Phonetic Distance from Critical-Band Spectra: A First Step, Proc. IEEE ICASSP'82, May, 1982, Vol. 2, pp. 1278-1281.
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