IJBTT

Performance Analysis Of Regularized Adaptive Algorithms For Noise Suppression In Speech Signals

	International Journal of Engineering Trends and Technology (IJETT)
	© 2017 by IJETT Journal
	Volume-44 Number-1
	Year of Publication : 2017
	Authors : G.Amjad Khan, Dr.K.E.Sreenivasa Murthy
	DOI :  10.14445/22315381/IJETT-V44P206

Citation 

G.Amjad Khan, Dr.K.E.Sreenivasa Murthy "Performance Analysis Of Regularized Adaptive Algorithms For Noise Suppression In Speech Signals", International Journal of Engineering Trends and Technology (IJETT), V44(1),28-31 February 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract
In this Paper, Regularized NLMS algorithm is proposed to enhance the speech signal from the noisy speech. Speech enhancement is a long standing problem with numerous applications like teleconferencing, VoIP, hearing aids and speech recognition degradations The motivation behind this research work is to obtain a clean speech signal of higher quality by applying the optimal noise cancellation technique. Real-time adaptive filtering algorithms seem to be the best candidate among all categories of the speech enhancement methods. Experiments were performed on noisy data which was prepared by adding AWGN, We then compare the noise cancellation performance of proposed Regularized NLMS algorithm with existing Spectral Subtraction method and NLMS algorithm in terms of Mean Squared Error (MSE), Signal to Noise ratio (SNR). Based on the performance evaluation, the proposed Regularized NLMS algorithm was found to be a better optimal noise cancellation technique in speech enhancement applications.

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Keywords
spectral Subtraction, Normalised NLMS, Regularised NLMS, SNR, MSE.