An improved wavelet-based speech enhancement system

Abstract

The problem of speech enhancement using wavelet thresholding algorithm is considered. Major problems in applying the basic algorithm are discussed and modifications are proposed to improve the method. First, we propose the use of different thresholds for different wavelet bands. Next, by employing a pause detection algorithm, noise profile is estimated and the thresholds are adapted. This enables the modified enhancement system to handle colored and nonstationary noises. Finally, a wavelet-based voiced/unvoiced classification is proposed and implemented that can further improve the performance of the enhancement system. To evaluate the system performance, we have used real-life noise types such as multi-talker babble and low-pass noises. Subjective and objective evaluations show that the proposed system improves the performance the wavelet thresholding algorithm.