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PERFORMANCE EVALUATION COMPARISON OF LMS AND NLMS ALGORITHM FOR AEC IN SPEECH PROCESSING

Shivangi Gupta, Madhav Singh, Ranbeer Tyagi

Abstract


ABSTRACT

An acoustic echo cancellation is a technique used to decrease the acoustic noise in corrupted speech signal. Adaptive filter is using to cancel the acoustic echoes. For better conversation in telecommunication application to achieve the control of acoustic echoes is important and for the proposed acoustic canceller echo algorithm is used to reduce unwanted noise. There is a requirement for more than thousands taps in acoustic echo path so this problem can be reduced by using different types of adaptive filtering technique namely, LMS and NLMS in MATLAB are executed. Based on convergence rates ERLE and computational complexity, the adaptive filtering algorithms like LMS, NLMS is used to cancel acoustic echo. Simulation results show that LMS algorithm has reduced convergence rate and least in complexity. The requirement of this algorithm uses an algorithm that has improved convergence rate and maintaining computational complexity, for this proposes NLMS algorithm is used, the limitation of this algorithm is very high computational complexity.

 

Keywords: Adaptive filter, LMS, NLMS, convergence rate, MSE and ERLE.

Cite this Article: Shivangi Gupta, Madhav Singh, Ranbeer Tyagi. Performance Evaluation Comparison of LMS and NLMS Algorithm for AEC in Speech Processing. International Journal Digital Communication and Analog Signals. 2019; 5(2): 9–19p.


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References


Nitika Gulbadhar, Shalini Bahel and Harmeet Kaur “Acoustic Echo Cancellation using LMS Algorithm” International Journal ofElectronics, Electrical and Computational System 2348-117X Volume 5, Issue 5 ,140-144 pp, May 2016

Fabián R. Jiménez L., Camilo E. PardoB, and Edgar A. Gutiérrez C. “Analysis Performance of Adaptive Filters for System Identification implemented over TMS320C6713 DSP Platform”presented at IEEE International Conf. on Digital Signal Processing, Vol.978, PP.4673-9461, Colombia,Jan .2015.

Sheng Zhang, Jiashu Zhang, and Hongyu “Robust variable step size decorrelation normalized least-mean-square and its application toacoustic echo cancellation” IEEE Signal Process. Mag., Vol. 29, No4PP.61–80, 2368 – 2376 pp, Jul. 2013.

Priyanka D N, Chandrashekar H M,” Implementation and Comparison of Echo Cancellation Algorithms using Adaptive Filtering Techniques in TMS320C6748 DSK” presented at IEEE International Conference On Recent Trends in Electronics Information & Communication Technology (RTEICT), May 19-20, 2017, Bangalore, India, India.

Donald Reay “Digital Signal Processing and Applications with the OMAP-L138 experimenter” ISBN:9781118228999, DOI:10.1002/9781118228999, 2012.

Rulph Chassaing “Digital Signal Processin and Applications with the C6713 and C6416 DSK” ISBN:9780471704072, DOI:10.1002/0471704075, 2005

SaharMobeen, IramBaig,andAnumRafique “Comparison Analysis Of Multi-Channel Echo Cancellation Using Adaptive Filters” IEEE International Conference on Open Source Systems and Technologies (ICOSST) Lahore, Pakistan, 2015.

Dubey, S.K., Rout, N.K., “FLMS algorithm for acoustic echo cancellation and its comparison with LMS” Recent Advances in Information Technology (RAIT), 2012, Dhanbad, India.

Abhishek Deb, Asutosh Kar and Mahesh Chandra, ―A Technical Review on Adaptive Algorithms for Acoustic Echo Cancellation‖, in proceedings of International Conference on Communication and Signal Processing, April 3-5, 2014, India, pp. 041-043.

Chandrakar C, Kowar MK. Denoising ECG signals using adaptive filter algorithm. International Journal of Soft Computing and Engineering (IJSCE). 2012 Mar; V 2(1):120-123pp.




DOI: https://doi.org/10.37628/jdcas.v5i2.1179

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