Speech enhancement based on adaptive wavelet denoising on multitaper spectrum

2008 ◽  
Author(s):  
Tai-Chiu Hsung ◽  
Daniel Pak-Kong Lun
Keyword(s):  
Speech Enhancement ◽  
Wavelet Denoising ◽  
Adaptive Wavelet ◽  
Multitaper Spectrum

scholarly journals Optimizing Signal De-Noising Algorithm for Acoustic Emission Leakage of Wavelet

2016 ◽  
Vol 16 (1) ◽  
pp. 116-125 ◽  
Author(s):  
Xin-Hua Wang ◽  
Yu-Lin Jiao ◽  
Yong-Chao Niu ◽  
Jie Yang
Keyword(s):  
High Pressure ◽  
Detection System ◽  
Minimum Mean Square Error ◽  
Weight Coefficient ◽  
Wavelet Denoising ◽  
Denoising Method ◽  
Adaptive Wavelet ◽  
Pressure Pipe ◽  
Optimal Linear ◽  
Mean Square Error Criterion

Abstract Traditional wavelet denoising method cannot eliminate complex high-pressure pipe signals effectively. In the updated wavelet adaptive algorithm, this thesis defines the constraints in order to reconstruct the signals accurately. According to the minimum mean square error criterion, the results predict the weight coefficient and get the optimal linear predictive value. Adopting the improved algorithm under the same condition, this thesis concluded that Db6 increased the complexity of wavelet algorithm by 50% by comparative experiments. It will be more conducive to the realization of hardware and the feasibility of real-time denoising. Dual adaptive wavelet denoising method improved SNR by 50%. This denoising method will play a key role in the detection rate of high-pressure pipe in the online leakage detection system.

Locally Adaptive Wavelet Thresholding for Speech Enhancement

2013 ◽  
Vol 380-384 ◽  
pp. 3618-3622
Author(s):  
Kang Liu ◽  
Jian Zheng Cheng ◽  
Li Cheng
Keyword(s):  
White Noise ◽  
Speech Enhancement ◽  
Speech Signal ◽  
Bayesian Framework ◽  
Threshold Function ◽  
Wavelet Thresholding ◽  
Wavelet Coefficients ◽  
Edge Preservation ◽  
Adaptive Wavelet ◽  
Locally Adaptive

There are strong dependencies between wavelet coefficients of speech signal,in this article,based on that,a new corresponding nonlinear threshold function derived in Bayesian framework is proposed to decrease the effect of the ambient noise.Analysis of the data shows the effectiveness of the proposed method that it removes white noise more effectually and gets better edge preservation.

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