Comparative Study of Wavelet and Wavelet Packet Transform for Denoising Telephonic Speech Signal
Author(s) -
G. Narendra Kumar,
Sugandh Kumar,
Nitendra Kumar
Publication year - 2015
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/19389-9145
Subject(s) - computer science , speech recognition , wavelet packet decomposition , wavelet , noise reduction , thresholding , discrete wavelet transform , speech enhancement , wavelet transform , mean squared error , pattern recognition (psychology) , artificial intelligence , mathematics , statistics , image (mathematics)
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 telephonic 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.
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