TY  - JOUR
T1  - A Noise Reduction Approach for Speech Signal Based on Stein’s Unbiased Risk Estimate
AU - Karthikeyan, S. AU - Kumar, P. Ganesh AU - Saran, K. 
JO  - Asian Journal of Information Technology
VL  - 12
IS  - 5
SP  - 154
EP  - 159
PY  - 2013
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2013.154.159
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2013.154.159
KW  - Wavelet thresholding
KW  -denoising
KW  -hilbert transform
KW  -mean square error
KW  -orthonormal
KW  -SNR
AB  - The proposed research in the denoising of speech signal is based on the concepts of Wavelet Thresholding by imposing quantum parameters. The idea of signal denoising is to preserve the signal features while reducing the noise level. Various denoising approaches exist in which wavelet-based point wise thresholding approaches are extensively adopted in many application fields like speech processing applications, medical applications, etc. For signal denoising based on wavelet thresholding, there are two decisive aspects, namely, the use of a proper thresholding function and the estimate of the noise standard deviation. Both greatly manipulate the quality of the denoised signal. In this study, a simple wavelet-based denoising approach is performed for real time speech signal which uses the modified linear expansion of thresholds based on Stein’s Unbiased Risk Estimation (SURE) and the noise standard deviation estimation depending on the number of vanishing moments of the wavelet transform. Investigational results demonstrate that higher Signal to Noise Ratio (SNR) with lower mean square error.
ER  -