Speech enhancement using adaptive wavelet shrinkage

I. Kim, Sung-il Yang, Y. Kwon
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引用次数: 16

Abstract

In this paper, the authors propose an adaptive wavelet threshold for noise cancellation. For this, they use a threshold value which minimizes Bayesian risk. And using entropy, they part the noisy signal into an unvoiced signal section and the other signal section is used to apply each the threshold value for each section. Experimental results show that proposed algorithm is more efficient.
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基于自适应小波收缩的语音增强
本文提出了一种自适应小波阈值去噪方法。为此,他们使用最小化贝叶斯风险的阈值。利用熵,他们将有噪声的信号分割成一个未发音的信号部分,另一个信号部分用于应用每个部分的阈值。实验结果表明,该算法具有较高的效率。
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