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  A Novel Technique for Speech Processing Using Combinational Adaptive Methods  
  Authors : M. Koteswara Rao; Dr I. Santhi Prabha
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This paper presents a new technic to introduce adaptive Filter with combinational Algorithm like Normalized LMS & variable stepsize LMS based on Shadow technic. Which is useful for the cancellation of the noise component mixed with Speech in the same frequency range, In this design proposed project implements an adaptive FIR filter,is based on the Shadow technic, which produces less mean square error and better convergence factor compare to LMS, here spectral characteristics of window is improved by shadow technic, finally de noised Speech is obtained at output, and also propose to calculate Signal to noise ratio values of shadow based Adaptive Filter with Normalized & variable stepsized LMS algorithm.


Published In : IJCSN Journal Volume 5, Issue 1

Date of Publication : February 2016

Pages : 165-170

Figures :09

Tables : 04

Publication Link : A Novel Technique for Speech Processing Using Combinational Adaptive Methods




M. Koteswara Rao : obtained M.Tech from JNTUK, Kakinada pursuing PhD from JNTU kakinada. He is having an experience more than 15 years and also having more number of both national and international journals, conferences. His area of interest is speech signal processing, presently working as associate professor in Sri Vasavi Engineering College, pedatadepalli, Tadepalligudem, A.P.

Dr. I. Santi Prabha : is working as Professor in ECE Department in Jawaharlal Nehru technological university ,kakinada, She did her B.Tech & M. Tech with specialization in Instrumentation and Control Systems from JNTU College of engineering, Kakinada. She was awarded with Ph.D. in Speech signal processing by Jawaharlal Nehru Technological University in 2005. She has 29 years experience of teaching to UG and PG classes and has received good response from the students. She has also 15 years of Research experience. She has produced two Ph.D. and guiding 7 Ph.D scholars. She has guided more than 50 M.Tech. projects. She is a member of I.S.T.E. and fellow member in I.E.T.E.& I.E. She has published 40 technical papers in national and International journals and conferences. She worked as Head of ECE Department and Deputy Warden for Lady’s hostel, JNTUK, KAKINADA,










Combinational LMS Algorithm

Shadow Technique

The Implementation of Adaptive-FIR Filter using shadow concept for Kaiser window was performed. we applied a noised speech signal to Adaptive filter and obtained de noised wave form at output which is shown in Fig-3. Later We shown responses of shadow based Adaptive filter from Fig:4 to Fig:6 for different shadow factors of the Normalized LMS algorithm. Similarly Fig:7 to Fig:9 for different shadow factors of the variable ste-sized Least mean square algorithm algorithm. Finally We compared SNR, mean square error(MSE) at input and Output which are shown from Table-1.,table-3 Respectively for Normalized LMS algorithm table-2 and Table-4 for variable step-sized Least mean square algorithm. From the above discussions it is concluded that shadow based adaptive filter produces better responses in terms of SNR and MSE compared to Normalized and variable step- sized LMS algorithm.










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