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  Develop and Validate RLS and Refined RLS Adaptive Filter Algorithm for Speech Enhancement  
  Authors : Mrinal Bachute; Dr. R D Kharadkar; Dr. S S Dorle
  Cite as:

 

One of the important means of communication is speech signal. In case of long distance communication it is important to maintain the quality of speech signal. The speech signal may get corrupted due to different types of noise. Hence, becomes a challenge to maintain high quality of speech signal [2]. Noise Cancellation is a technique used for reducing undesired noise signal. Communication has become an integral part of our life. The paper aims to investigate performance of recursive least square adaptive algorithms in speech enhancement application. Objective of Implementing and analyzing the algorithms is to modify the algorithm to improve convergence behaviour, reduce computational requirements and decrease steady state mean square error. Experimental results revel that modified RLS algorithms perform better than the existing algorithms.

 

Published In : IJCSN Journal Volume 4, Issue 5

Date of Publication : October 2015

Pages : 785 - 792

Figures :09

Tables : 07

Publication Link : Develop and Validate RLS and Refined RLS Adaptive Filter Algorithm for Speech Enhancement

 

 

 

Mrs. M. R. Bachute : is research scholar of G. H. Raisoni College of Engineering, Nagpur, Maharashtra, India. She has completed her ME (Digital Electronics) from College of Engineering, Badnera, Amravati Maharashtra. Currently she pursuing her PhD from RTM University Nagpur, Maharashtra and working as a Assistant Professor at G. H. Raisoni Institute of Engineering and Technology, Pune, Maharashtra. She has teaching experience of 15 years. She has guides UG and PG students for the projects. Her area of working is Digital Signal Processing and Adaptive Signal Processing. She has attended National & International workshops and conferences. Mrs. M. R. Bachute is life member of ISTE, IE (India) and IEEE

Dr. R. D. Kharadkar : is Professor in Electronics and Telecommunication Engineering at University of Pune, Pune Maharashtra. He completed his ME (Electronics) and PhD from Shivaji University, Kolhapur, Maharashtra. His field of working is in Digital Signal Processing and Networking. He is Principal at G. H. Raisoni Institute of Engineering and Technology, Pune, Maharashtra. He is senior member of IEEE. He has teaching and industrial experience of 30 years. He has also worked with Tata Motors, Pune, Maharashtra. He has published papers in National, International journals and conferences. He guides the ME and PhD students. He chaired National and International conference sessions. Dr. R. D. Kharadkar is currently working as a member of Board of Studies and Faculty of Technology at University of Pune, Maharashtra. He is a life member of ISTE, IETE, IE and ISIO.

Dr. S. S. Dorle : is Professor and Head in Electronics Engineering Department at G. H. Raisoni College of Engineering, Nagpur, Maharashtra. He completed his M.Tech (EDT) and Ph.D from VNIT, Nagpur, Maharashtra. His field of working is Adhoc Networks. He has 15 years of teaching experience. He has published papers in National, International journals and conferences. He guides the ME and PhD students. He worked as resource person for various STTP, seminars and workshops. He worked as reviewer for various International Journals. Dr. S. S. Dorle is life member ISTE, CSI, fellow of IETE and member of IEEE.

 

 

 

 

 

 

 

RLS

Modified RLS

Speech Enhancement

SNR

The Experimental results reveal that the RLS algorithm has minimum MSE and maximum SNR as compared to LMS but at a cost of increased computational complexity. Modified RLS provides even better SNR as compared to existing RLS algorithm. The test is performed at 0dB, 5dB and 10dB airport noise. The experimentation and validation are carried out for Mean Square Error (MSE) ,SNR and execution time. The experimentation and validation is carried out for modified RLS and is compared with existing methods and it is observed that modified method performs better as compared to existing methods.

 

 

 

 

 

 

 

 

 

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