Single Channel Speech Enhancement for Mixed Non-stationary Noise Environments

Abstract

Speech enhancement is very important step for improving quality and intelligibility of noisy speech signal. In practical environment more than one noise sources are present, hence it is necessary to design a technique/ algorithm that can remove mixed noises or more than one noises from single-channel speech signals. In this paper, a single channel speech enhancement method is proposed for reduction of mixed non-stationary noises. The proposed method is based on wavelet packet and ideal binary mask thresholding function for speech enhancement. Db10 mother wavelet packet transform is used for decomposition of speech signal in three levels. After decomposition of speech signal a binary mask threshold function is used to threshold the noisy coefficients from the noisy speech signal coefficients. The performance of the proposed wavelet with ideal mask method is compared with Wiener, Spectral Subtraction, p-MMSE, log-MMSE, Ideal channel selection, Ideal binary mask, hard and soft wavelet thresholding function in terms of PESQ, SNR improvement, Cepstral Distance, and frequency weighted segmental SNR. The proposed method has shown improved performance over conventional speech enhancement methods.