Research Article
Speech denoising in the presence of Impulsive Noise
@INPROCEEDINGS{10.4108/eai.13-7-2017.2270053, author={Ruibo Zhang and Hongqing Liu and Zhen Luo and Yi Zhou}, title={Speech denoising in the presence of Impulsive Noise}, proceedings={10th EAI International Conference on Mobile Multimedia Communications}, publisher={EAI}, proceedings_a={MOBIMEDIA}, year={2017}, month={12}, keywords={speech denosing impulsive noise sparsity joint estimation}, doi={10.4108/eai.13-7-2017.2270053} }- Ruibo Zhang
Hongqing Liu
Zhen Luo
Yi Zhou
Year: 2017
Speech denoising in the presence of Impulsive Noise
MOBIMEDIA
EAI
DOI: 10.4108/eai.13-7-2017.2270053
Abstract
This work addresses speech denoising problem in the presence of impulsive noise in transform domains. The impulsive noise, in this work, is modeled by an unknown sparse vector so that it can be actively suppressed. The speech signal is sparsely represented by the wavelet domain. To achieve the simultaneous speech recovery and the noise suppression, a joint estimation is devised based on the fact they have sparse representations in different domains. To efficiently solve the problem, the alternating direction method of multipliers (ADMM) is adopted to obtain the solution. Simulation results demonstrate the superior performance of the proposed approach.
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