An Improvement in Speech Signals Corrupted by Impulsive Noise using Wavelets Wiener Filter and ICA Technique
نویسنده
چکیده
The aim of this paper is to investigate the effect of noises on performance of speech signal de-noising using the method based on wavelets, wiener filtering and ICA. Determination of voiced and unvoiced speech, low and high pitch, and methods for selecting appropriate wavelets for speech compression are discussed. Discrete wavelet transform (DWT) has been applied for suppression of additive noise. Soft thresholding are used in the process to detect time occurrence of noise corrupting the signal. Based on the number of samples at a stretch that are corrupted, wiener filter with a variable size window compressed them by wavelet transform then create an Improved ICA (Independent component analysis) technique which will remove artifacts of speech signal. The results of stimulation show that proposed techniques provide enhancement in quality and intelligibility of speech signal. Index Terms – Speech signal, noises, wavelet transform, wiener filter, short time energy, spectral centroid, ICA.
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