A Novel Wavelet Packet Speech Enhancement Algorithm Based On Time-Frequency Threshold

2007 ◽  
Author(s):  
Yaohua Xu ◽  
Gang Wang ◽  
Ying Gu ◽  
Haiyang Liu
Keyword(s):  
Speech Enhancement ◽  
Wavelet Packet ◽  
Time Frequency ◽  
Frequency Threshold ◽  
Enhancement Algorithm

A Non-Contact Speech Enhancement Algorithm Based on Wavelet Packet Adaptive Threshold

2012 ◽  
Vol 241-244 ◽  
pp. 194-198
Author(s):  
Hui Jun Xue ◽  
Sheng Li ◽  
Teng Jiao ◽  
Guo Hua Lu ◽  
Yang Zhang ◽  
...  
Keyword(s):  
Speech Enhancement ◽  
Speech Signal ◽  
Wavelet Packet ◽  
Wiener Filter ◽  
Adaptive Threshold ◽  
Human Communication ◽  
Frequency Signal ◽  
Time Frequency ◽  
Detecting Method ◽  
Enhancement Algorithm

Speech is an important method for human communication. In this paper, we developed a new method for detecting speech signal. Because of the advantage of this speech detecting method, it has great potential application value in many fields. Simultaneously, basing on the good capability of wavelet packet for analyzing time-frequency signal, this paper also developed an algorithm of wavelet packet threshold by using hard threshold and soft threshold for removing noise. Comparing to spectral subtraction and Wiener filter speech enhancement algorithm, the proposed algorithm takes on a better performance on noise removing and speech signal reserving.

The Energy Distribution of Tire-Road Noise and Noisy Speech Based on Wavelet Packet

2011 ◽  
Vol 464 ◽  
pp. 721-724 ◽  
Author(s):  
Zhi Yong He ◽  
Li Heng Luo
Keyword(s):  
Energy Distribution ◽  
Speech Enhancement ◽  
Mobile Communications ◽  
Wavelet Packet ◽  
Noise Signal ◽  
Wavelet Packets ◽  
Road Noise ◽  
Noisy Speech ◽  
Time Frequency ◽  
The Difference

Speech enhancement is very important for mobile communications or some other applications in car. The energy distribution of signal is the basis of algorithms which denoise noisy speech in time-frequency domain. In this work, the noise regarded is the tire-road noise when driving in expressway. Wavelet packets transform is used in the analysis. After decomposing noise signal and noisy speech signal by wavelet packet transform, the analysis for the difference of the energy distribution between noisy speech and noise is finished.

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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