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

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Comparative Study of Wavelet and Wavelet Packet Transform for Denoising Telephonic Speech Signal

by Gautam Kumar, Sugandh Kumar, Nitendra Kumar
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 110 - Number 15
Year of Publication: 2015
Authors: Gautam Kumar, Sugandh Kumar, Nitendra Kumar
10.5120/19389-9145

Gautam Kumar, Sugandh Kumar, Nitendra Kumar . Comparative Study of Wavelet and Wavelet Packet Transform for Denoising Telephonic Speech Signal. International Journal of Computer Applications. 110, 15 ( January 2015), 1-8. DOI=10.5120/19389-9145

@article{ 10.5120/19389-9145,
author = { Gautam Kumar, Sugandh Kumar, Nitendra Kumar },
title = { Comparative Study of Wavelet and Wavelet Packet Transform for Denoising Telephonic Speech Signal },
journal = { International Journal of Computer Applications },
issue_date = { January 2015 },
volume = { 110 },
number = { 15 },
month = { January },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume110/number15/19389-9145/ },
doi = { 10.5120/19389-9145 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:46:24.720865+05:30
%A Gautam Kumar
%A Sugandh Kumar
%A Nitendra Kumar
%T Comparative Study of Wavelet and Wavelet Packet Transform for Denoising Telephonic Speech Signal
%J International Journal of Computer Applications
%@ 0975-8887
%V 110
%N 15
%P 1-8
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In communication systems and other speech related systems, background noise is a severe problem. The speech signal gets polluted by the noises that are from transmission medium and surroundings. Noise degrades the quality and the intelligibility of the speech signals. Addition of noise is by various factors like heavy machines, pumps, vehicles, using radio communication device or over noisy telephone channel. The basic idea behind the project work is to denoise the noisy telephonic speech signal. This work is based on studying and implementing wavelets as denoising algorithm. The Wavelet Transform (WT) and Wavelet Packet Transform (WPT) implemented for the work is Discrete. Haar, Daubechies, Symlet and Coiflet wavelets are implemented for denoising of telephonic speech signal. Performance of speech signal is evaluated on the basis of SNR (signal to noise ratio) and RMSE (root mean square error). SNR and RMSE are calculated for both Soft Thresholding and Hard Thresholding.

References
  1. Dr. Mahesh S. Chavan, Mrs. Manjusha N. Chavan and Dr. M. S. Gaikwad 2010, "Studies on Implementation of Wavelet for De-noising Speech Signal", International Journal of Computer Applications (0975-8887) Volume 3-No. 2, pp 1-7.
  2. Dr. Parvinder Singh Dinesh Singh and Deepak Sethi, 2011, "Reduction of Noise from Speech Signal using Haar and Biorthogonal Wavelet", IJECT Vol. 2, Issue 3, pp 263-269.
  3. Soon Ing Yann, 2003, "Transform based Speech Enhancement Techniques", PhD Thesis, Nanyang Technological University, pp 1-4.
  4. Mahesh S. Chavan and Nikos Mastorakis, 2010, "Studies on implementation of Haar and Daubechies Wavelet for Denoising of Speech Signal", International Journal of Circuits, Systems and Signal Processing, Issue 3, Volume 4, pp 83-96.
  5. Slavy G. Mihov Ratcho M. Ivanov and Angel N. Popov, 2009, "De-noising Speech Signals by Wavelet Transform", Annual Journal of Electronics, ISSN 1313-1842.
  6. M. Siffuzzaman, M. R Islam and M. Z. Ali, 2009, "Application of Wavelet Transform and its Advantages Compared to Fourier Transform", Journal of Physical Sciences, ISSN: 0972-8791, Vol. 13, pp 121-134.
  7. S. Salivahanan and C. Gnanapriya "Digital Signal Processing", Tata McGraw Hill, Second Edition.
  8. Roopali Goel and Javed Ahmed, 2013 "Contrast of Wavelets Order Behavior for Sine Signal", International Journal of Innovative Technology and Exploring Engineering (IJITEE), ISSN: 2278-3075, Volume-2, Issue-6, pp 287-290.
  9. Nitendra Kumar, Prof. A. H. Siddiqi and Dr. Khursheed Alam, 2014, "Raman Spectral Data De-noising Based On Wavelet Analysis", International Journal of Computer Application (IJCA), Vol. (102).
  10. Wang Na, Zheng Dezhong, Xu Shuang and Zhang Shuqing, 2008, "A New Algorithm For Speech Enhancement Using Wavelet Packet Transform Based on Auditory Model", International Conference on Computer Science and Software Engineering, IEEE Computer Society, 978-0-7695-3336-0/08, pp 1000-1003.
  11. Sai Lakshmi Bhamidipati, Sai Sudha Mindagudla, Harsha Vardhan Devalla, Hima Sagar Goodi and Hemanth Nag, 2014, "Analysis of Different Discrete Wavelet Transform Basis Functions in Speech Signal Compression", IOSR Journal of VLSI and Signal Processing (IOSR-JVSP), e-ISSN: 2319-4200, p-ISSN No. : 2319-4197, Volume 4, Issue (1), pp 34-38.
  12. V. S. R Kumari and Dileep Kumar Devarakonda, 2013, "A Wavelet Based Denoising of Speech Signal", International Journal of Engineering Trends and Technology (IJETT), ISSN: 2231-5381, Volume 5 No. (2), pp 107-114.
  13. Mahesh S. Chavan, Nikos Mastorakis, Manjusha N. Chavan and M. S. Gaikwad "Implementation of SYMLET Wavelets to Removal of Gaussian Additive Noise from Speech Signal", Recent Researches in Communications, Automations, Signal Processing, Nanotechnology, Astronomy and Nuclear Physics, ISBN: 978-960-474-276-9, pp 37-41.
Index Terms

Computer Science
Information Sciences

Keywords

Wavelet Wavelet Packet Transform Thresholding.

Powered by PhDFocusTM