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Enhancement of Speech Signal using Improved NLMS Algorithm

by Rathnakara.S, V. Udayashankara
Communications on Applied Electronics
Foundation of Computer Science (FCS), NY, USA
Volume 6 - Number 9
Year of Publication: 2017
Authors: Rathnakara.S, V. Udayashankara
10.5120/cae2017652557

Rathnakara.S, V. Udayashankara . Enhancement of Speech Signal using Improved NLMS Algorithm. Communications on Applied Electronics. 6, 9 ( Apr 2017), 34-37. DOI=10.5120/cae2017652557

@article{ 10.5120/cae2017652557,
author = { Rathnakara.S, V. Udayashankara },
title = { Enhancement of Speech Signal using Improved NLMS Algorithm },
journal = { Communications on Applied Electronics },
issue_date = { Apr 2017 },
volume = { 6 },
number = { 9 },
month = { Apr },
year = { 2017 },
issn = { 2394-4714 },
pages = { 34-37 },
numpages = {9},
url = { https://www.caeaccess.org/archives/volume6/number9/720-2017652557/ },
doi = { 10.5120/cae2017652557 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-09-04T19:57:00.849601+05:30
%A Rathnakara.S
%A V. Udayashankara
%T Enhancement of Speech Signal using Improved NLMS Algorithm
%J Communications on Applied Electronics
%@ 2394-4714
%V 6
%N 9
%P 34-37
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper a modified robust variable step size algorithm is proposed and the performance of the proposed algorithm is compared with original robust variable step size (RVSS) algorithm. This leads to another derivative of Normalized Least mean square algorithm (NLMS). The performance of the proposed algorithm is measured with additive stationary and nonstationary Gaussian noise with original speech taken by standard IEEE sentence (SP23) of NOIZEUS data base. The output of proposed and RVSS algorithm are measured with excess mean square error (EMSE) in both stationary and non stationary environment. The results can be appreciated that the proposed algorithm gives improved result over RVSS algorithm and also the speed of convergence is maintained same as other NLMS algorithms

References
  1. Alexander D.Poularikas, Zayed M.Ramadan “Adaptive filtering primer with MATLAB CRC press
  2. Zayed Ramadan, &Alexander Poularikas ,Performance Analysis of a New Variable Step-Size LMS Algorithm with Error Nonlinearities IEEE 2004 pp384-388
  3. Zayed Ramadan and Alexander Poularikas A Robust Variable Step-Size LMS Algorithm Using Error-Data Normalization IEEE 2005 PP219-224
  4. Zayed Ramadan and Alexander Poularikas A Variable Step-Size Adaptive Noise Canceller Using Signal to Noise Ratio as the Controlling Factor IEEE2004 PP 456-461
  5. Zayed Ramadan and Alexander Poularikas An Adaptive Noise Canceller Using Error Nonlinearities in the LMS Adaptation IEEE 2004 pp3-8
  6. Joonwan Kim &Alexander D. Poularikas “Performance analysis of the Adjusted step size NLMS algorithm IEEE 2004 pp 467-571
  7. Ma Shengqian, Xu Guowei, Ma Zhifeng, Wei Shuping, Fan Manhong “Research on adaptive noise canceller of an improvement LMS algoritnm 2011 IEEE pp1611-1614
  8. V.Udayashankara “ Modern digital signal processing” second edition PHI
  9. Simon Haykin “ Adaptive Filter Theory” Fourth edition pearson education
Index Terms

Computer Science
Information Sciences

Keywords

Speech enhancement noise estimation NLMS RVSS EMSE