Abstract：Aiming at the problem of speech signal de-noising, this paper
presents an adaptive threshold de-noising method based on wavelet
entropy. The method decomposes speech signal with noise by wavelet
transform, and calculates wavelet entropy of the decomposed signal
in each wavelet sub-interval. It combines the wavelet entropy with
adaptive threshold to determine the threshold of high frequency
coefficients. Compromised index threshold function is proposed to
denoise the speech signal, and then the denoised signal is
reconstructed. Finally, the paper compares the de-noising
performance of the proposed threshold method, minimaxi threshold
method, sqtwolog threshold method, and rigrsure threshold method.
The simulation results show that when the input Signal-to-noise
Ratio (SNR) is 7 dB, the output SNR with the proposed threshold
de-noising method is the largest, and the input and output SNR curve
is higher than what the other three kinds of threshold de-noising
methods have, which proves that this method has better de-noising
performance.
Xiaojuan Chen;Siyang Li;Wenting Wang. New De-noising Method for Speech Signal Based on Wavelet Entropy and Adaptive Threshold[J]. , 2015, 12(3): 1257-1265.
Xiaojuan Chen;Siyang Li;Wenting Wang. New De-noising Method for Speech Signal Based on Wavelet Entropy and Adaptive Threshold. , 2015, 12(3): 1257-1265.
2015, Vol. 12 
