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.
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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