Open Science Research Excellence
@article{(International Science Index):,
  title    = {Adaptive Noise Reduction Algorithm for Speech Enhancement},
  author    = {M. Kalamani and  S. Valarmathy and  M. Krishnamoorthi},
  country   = {India},
  institution={Bannari Amman Institute of Technology},
  abstract  = {In this paper, Least Mean Square (LMS) adaptive
noise reduction algorithm is proposed to enhance the speech signal
from the noisy speech. In this, the speech signal is enhanced by
varying the step size as the function of the input signal. Objective and
subjective measures are made under various noises for the proposed
and existing algorithms. From the experimental results, it is seen that
the proposed LMS adaptive noise reduction algorithm reduces Mean
square Error (MSE) and Log Spectral Distance (LSD) as compared to
that of the earlier methods under various noise conditions with
different input SNR levels. In addition, the proposed algorithm
increases the Peak Signal to Noise Ratio (PSNR) and Segmental SNR
improvement (ΔSNRseg) values; improves the Mean Opinion Score
(MOS) as compared to that of the various existing LMS adaptive
noise reduction algorithms. From these experimental results, it is
observed that the proposed LMS adaptive noise reduction algorithm
reduces the speech distortion and residual noise as compared to that
of the existing methods.
    journal   = {International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering},  volume    = {8},
  number    = {6},
  year      = {2014},
  pages     = {1014 - 1021},
  ee        = {},
  url       = {},
  bibsource = {},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 90, 2014},