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| An Adaptive Speech Signal De-noising Algorithm Based on Estimation of Scaled Noise Energy |
| XIE Wei-Sheng, YANG Gen-Ke |
| (Department of Automation, Key Laboratory of System Control and Information Processing, Ministry of Education, Shanghai Jiaotong University, Shanghai 200240, China) |
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Abstract A novel scheme of wavelet thresholding for speech signal de-noising was proposed. The scheme introduces a new thresholding function to overcome the drawbacks of traditional soft and hard thresholding functions. This newly introduced function is continuous at the threshold, so that it can curb the pseudogibbs phenomena effectively. Besides, it can reduce constant bias between the original wavelet coefficient and the estimated one, which helps to preserve the feature of the signal. With this threshold function, an adaptively selective algorithm of wavelet threshold was then proposed. This algorithm has both the virtues of spatial selective noise filtration method and the traditional threshold denoising method. It takes advantage of the inter-scale correlations of the wavelet coefficients to estimate the energy of scaled noise signal. In this algorithm, the threshold in each scale is selected based on the scaled noise energy. The simulations demonstrate that the proposed method is superior to some other existing adaptive wavelet de-noising methods.
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Received: 14 September 2011
Published: 28 September 2012
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