一种增强有色噪声干扰语音的预白化子空间方法

Q. Wei, Youshen Xia, Shubiao Jiang
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引用次数: 10

摘要

在本文中,我们提出了一种改进的子空间方法,用于彩色噪声存在下的语音增强,该方法基于一种新的预白化技术。首先将有色噪声建模为自回归(AR)过程,用于AR参数估计。然后通过将噪声语音与AR参数构造的白化矩阵相乘,将有色噪声下的语音模型转换为白噪声下的语音模型。由于采用了新颖的预白技术,所提出的子空间语音增强方法可以有效地处理有色噪声。与现有的子空间方法相比,本文提出的子空间方法克服了彩色噪声协方差矩阵估计的困难。仿真结果表明,该方法比三种传统算法具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel prewhitening subspace method for enhancing speech corrupted by colored noise
In this paper, we propose an improved subspace method for speech enhancement in the presence of colored noise, based on a novel prewhitening technique. The colored noise modeled as autoregressive (AR) process is first used for the AR parameter estimation. Then the speech model in colored noise is changed into the one in white noise, by multiplying the noisy speech by the whitening matrix constructed by the AR parameters. Because of the novel prewhitening technique, the proposed subspace method for speech enhancement can efficiently deal with colored noise. Compared with existing subspace method, the proposed subspace method overcomes difficulty in estimating covariance matrix of colored noise. Simulation shows that the proposed approach has better performance than three conventional algorithms.
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