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Optimal Adaptive Filtering Technique for Tamil Speech Enhancement

by Vimala.c, Radha.v
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 41 - Number 17
Year of Publication: 2012
Authors: Vimala.c, Radha.v
10.5120/5633-7996

Vimala.c, Radha.v . Optimal Adaptive Filtering Technique for Tamil Speech Enhancement. International Journal of Computer Applications. 41, 17 ( March 2012), 23-29. DOI=10.5120/5633-7996

@article{ 10.5120/5633-7996,
author = { Vimala.c, Radha.v },
title = { Optimal Adaptive Filtering Technique for Tamil Speech Enhancement },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 41 },
number = { 17 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 23-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume41/number17/5633-7996/ },
doi = { 10.5120/5633-7996 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:29:50.727121+05:30
%A Vimala.c
%A Radha.v
%T Optimal Adaptive Filtering Technique for Tamil Speech Enhancement
%J International Journal of Computer Applications
%@ 0975-8887
%V 41
%N 17
%P 23-29
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Noise reduction in speech applications has a significant amount of research for several decades. The ultimate goal of the speech signal processing research is to develop systems which can perform well in noisy environments. The main objective of this research work is to obtain a clean speech signal of higher quality by applying the optimal noise cancellation technique. In recent years, the real-time adaptive filtering algorithms are considered to be an essential technique for noise cancellation. In this paper, the most popular adaptive filtering algorithms namely Least Mean Square (LMS), Normalized Least Mean Squares (NLMS) and Recursive Least Squares (RLS) algorithms are analyzed and implemented for Tamil speech enhancement. Based on the experimental results, it can be observed that the performance of the adaptive filters is better than using conventional methods designed for speech enhancement. The performances of these algorithms are evaluated based on the metrics namely PSNR, MSE, SNR and SNR Loss. Based on the performance evaluation, the RLS algorithm was found to be a better optimal noise cancellation technique for Tamil speech signals.

References
  1. Georgi Iliev and Nikola Kasabov, "Adaptive Filtering with Averaging in Noise Cancellation for Voice and Speech Recognition", Department of Information Science, University of Otago.
  2. V. JaganNaveen, T. prabakar, J. Venkata Suman , P. Devi Pradeep, "Noise suppression in speech signals using adaptive algorithms", International Journal of Signal Processing, Image Processing and Pattern Recognition,Vol. 3, No. 3, September, 2010.
  3. Jan Vanus and Vitezslav Stkskala,"Application of optimal settings of the LMS adaptive filter for speech signal prosessing", Procedings of the International multiconference on Computer Science and Information Technology pp. 767-774, ISBN 978-83-60810-27-9,ISSN 1896-7094.
  4. Jan Vanus, "The use of the adaptive noise cancellation for voice Communication with the control system", International Journal of Computer Science and Applications,Technomathematics Research Foundation,Vol. 8, No. 1, pp. 54 – 70, 2011.
  5. Jianfen Maa b, Philipos C. Loizou b,"SNR loss: A new objective measure for predicting the intelligibility of noise-suppressed speech", J. Ma, P. C. Loizou / Speech Communication 53 (2011) 340–354.
  6. Komal R. Borisagar and Dr. G. R. Kulkarni,"Simulation and Comparative Analysis of LMS and RLS Algorithms Using Real Time Speech Input Signal", Global Journal of Researches in Engineering, Page 44,Vol. 10,Issue,5 (Ver1. 0)October2010.
  7. D. Prabhakara Rao,Sri M. Koteswararao, Dr. I. Santhi Prabha, "Combinational Adaptive Filter Technique for Speech Enhancement", IJECT Vol. 2, SP-1, Dec . 2011, ISSN : 2230-7109(Online) | ISSN : 2230-9543(Print).
  8. Sayed. A. Hadei, Student Member IEEE and M. lotfizad, "A Family of Adaptive Filter Algorithms in Noise Cancellation for Speech Enhancement", International Journal of Computer and Electrical Engineering, Vol. 2, No. 2, April 2010,1793-8163.
  9. Simon Haykin,"Adaptive Filter Theory", prentice hall of india,4th Edition.
  10. Siva Prasad Nandyala and T. Kishore Kumar, "Speech Enhancement Using Kernel Adaptive Filtering Method", Microwaves, Communications, Antennas and Electronics Systems (COMCAS), 2011 IEEE International Conference on, 10. 1109/COMCAS. 2011. 6105874 , ISBN: 978-1-4577-1692-8.
  11. A. Srinivasan, "Adaptive Echo Noise Elimination for Speech Enhancement of Tamil letter 'Zha'", International Journal of Engineering and Technology Vol. 1 (3), 2009, 91-97, ISSN: 0975-4024.
  12. L. Stasionis, A. Serackis , "Selection of an Optimal Adaptive Filter for Speech Signal Noise Cancellation using C6455 DSP", Electronics And Electrical Engineering, ISSN 1392 – 1215, 2011. No. 9(115).
Index Terms

Computer Science
Information Sciences

Keywords

Tamil Speech Noise Cancellation Adaptive Filter Lms Nlms Rls Speech Enhancement Snr And Snr Loss

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