A New Algorithm for Speech Enhancement Using Wavelet Packet Transform Based on Auditory Model

2008 ◽  
Author(s):  
Wang Na ◽  
Zheng Dezhong ◽  
Xu Shuang ◽  
Zhang Shuqing
Keyword(s):  
Speech Enhancement ◽  
Wavelet Packet ◽  
Wavelet Packet Transform ◽  
Auditory Model

scholarly journals Wavelet Packet Transform based Speech Enhancement via Two-Dimensional SPP Estimator with Generalized Gamma Priors

2016 ◽  
Vol 41 (3) ◽  
pp. 579-590 ◽  
Author(s):  
Pengfei Sun ◽  
Jun Qin
Keyword(s):  
Speech Enhancement ◽  
Wavelet Packet ◽  
Minimum Mean Square Error ◽  
Wavelet Packet Transform ◽  
Perceptual Quality ◽  
Two Dimensional ◽  
Noisy Environments ◽  
Time Frequency ◽  
Generalized Gamma ◽  
Speech Model

Abstract Despite various speech enhancement techniques have been developed for different applications, existing methods are limited in noisy environments with high ambient noise levels. Speech presence probability (SPP) estimation is a speech enhancement technique to reduce speech distortions, especially in low signalto-noise ratios (SNRs) scenario. In this paper, we propose a new two-dimensional (2D) Teager-energyoperators (TEOs) improved SPP estimator for speech enhancement in time-frequency (T-F) domain. Wavelet packet transform (WPT) as a multiband decomposition technique is used to concentrate the energy distribution of speech components. A minimum mean-square error (MMSE) estimator is obtained based on the generalized gamma distribution speech model in WPT domain. In addition, the speech samples corrupted by environment and occupational noises (i.e., machine shop, factory and station) at different input SNRs are used to validate the proposed algorithm. Results suggest that the proposed method achieves a significant enhancement on perceptual quality, compared with four conventional speech enhancement algorithms (i.e., MMSE-84, MMSE-04, Wiener-96, and BTW).

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