CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Improving Speech Signal Intelligibility by Optimal Computation using Single-Channel Adaptive Filtering

by Ohidujjaman, Mahmudul Hasan, Mohammad Nurul Huda
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 106 - Number 9
Year of Publication: 2014
Authors: Ohidujjaman, Mahmudul Hasan, Mohammad Nurul Huda
10.5120/18547-9790

Ohidujjaman, Mahmudul Hasan, Mohammad Nurul Huda . Improving Speech Signal Intelligibility by Optimal Computation using Single-Channel Adaptive Filtering. International Journal of Computer Applications. 106, 9 ( November 2014), 15-21. DOI=10.5120/18547-9790

@article{ 10.5120/18547-9790,
author = { Ohidujjaman, Mahmudul Hasan, Mohammad Nurul Huda },
title = { Improving Speech Signal Intelligibility by Optimal Computation using Single-Channel Adaptive Filtering },
journal = { International Journal of Computer Applications },
issue_date = { November 2014 },
volume = { 106 },
number = { 9 },
month = { November },
year = { 2014 },
issn = { 0975-8887 },
pages = { 15-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume106/number9/18547-9790/ },
doi = { 10.5120/18547-9790 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:38:56.437782+05:30
%A Ohidujjaman
%A Mahmudul Hasan
%A Mohammad Nurul Huda
%T Improving Speech Signal Intelligibility by Optimal Computation using Single-Channel Adaptive Filtering
%J International Journal of Computer Applications
%@ 0975-8887
%V 106
%N 9
%P 15-21
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Numerous environmental sources of noise and distortion can degrade the quality of the speech signal in a communication system. This study explores the effects of these intrusive sounds on speech applications, introduces some techniques for reducing the influence of noise and enhances the acceptability and intelligibility of the speech signal. In our research, a noise reduction system incorporates a single microphone method in time domain to improve SNRs (signal to noise ratios) of noise contaminated speech. Previously, noise reduction techniques estimate noise from the valley of the spectrum based on the harmonic properties of noisy speech, called minimum value sequences (MVS). Since the valleys of spectrum are inadequate to estimate noise reliably, we propose the estimated degree of noise (EDON) [1], [2] to adjust the amplitudes of the MVS. The salient features of the proposed method are a single-channel adaptive filter to reduce computational time and cost for optimal noise reduction, and to estimate noise continuously on a frame-by-frame basis without the aid of voice activity detector (VAD) [2]. For optimal noise reduction with a fewer number of iterations, an equation is derived from set values of SNRs and EDONs. To derive the proposed iteration number equation, we use the third degree parabola equation and least squares solution for the coefficients of EDON.

References
  1. Hamid, M. E. , Hasan, M. , Inamurrahman, M. , and Ghribi,W. , "An Improved Sad Algorithm of Noisy Speech Using Estimated Degree of Noise",canadian journal on signal processing issn: 1923-1709, july 15, 2011, canada.
  2. Hasan, M. , Hamid, M. E. ," A parametric formulation to Detect Speech Activity of noisy speech using EDON"; iccit – 2010, iccit – 2010, paper id-155, page- 252 - 255; 23-25 december, 2010, dhaka, bangladesh.
  3. Huang, Y. , and Benesty, J. , Audio Signal Processing for Next-Generation Multimedia Communication Systems, Kluwer Academic Publishers, 2004.
  4. Lim, J. S. , and Oppenheim, A. V. , "All-pole Modeling of Degraded Speech," IEEE Trans. Acoust. , Speech Signal Process. , vol 26, pp 197- 210, June 1978.
  5. Jutten, C. , and Hérault, J. , "Independent Component Analysis versus Principal Component Analysis", Signal Processing IV, pp. 643-646, 1988.
  6. Thi, H. L. N. , and Jutten, C. , "Blind Source Separation for Convolutive Mixtures", Signal Processing, vol. 45, pp. 209-229, 1995.
  7. Hamid, M. E. , Ogawa, K. , and Fukabayashi, T. , "Improved Single Channel Noise Reduction Method of Speech by Blind Source Separation", Acoust. Sci. & tech. , Japan.
  8. Hamid, M. E. , and Fukabayashi, T. , "A Two-Stage Method for Single-Channel Speech Enhancement", IEICE Trans. Fundamentals, vol. E89-A, no. 4, pp. 1058-1068, April 2006.
  9. Hamid, M. E. , and Fukabayashi, T. , "Noise Reduction of Speech Signal using Noise Subtraction and Blind Source Separation", Annual Report of Graduate School of Electronic Science and Technology, Shizuoka University, vol. 27, pp. 31-37, 2006.
  10. Hamid, M. E. , Ogawa, K. , and Fukabayashi, T. , "Performance of Two-Stage Noise Reduction Method by Iteration Number of Separation Filter Update in Processing Block", Proc. Technical Report of IEICE, pp. 19-24, Wakayama, January 2006.
  11. Hamid, M. E. , Ogawa, K. , and Fukabayashi, T. , "Improvement of Nose Reduction of Speech using Blind Signal Separation",Proc. ASJ spring meeting, pp. 639-640, Tokyo, March 2006.
  12. Hamid, M. E. , Ogawa, K. , and Fukabayashi, T. , "Wide Band Noise Reduction of Speech using Noise Subtraction and Blind Source Separation", Proc. WESPAC IX, Seoul, June 2006.
  13. TIMIT Acoustic-Phonetic Continuous Speech Corpus site https://catalog. ldc. upenn. edu/LDC93S1.
Index Terms

Computer Science
Information Sciences

Keywords

Adaptive filter degree of noise enhancement iteration number noise speech signal signal to noise ratio

Powered by PhDFocusTM