基于泄漏LMS算法的正弦降噪方法

Teppei Washi, A. Kawamura, Y. Iiguni
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引用次数: 3

摘要

先前已经提出了一种使用预测误差滤波器来减少含噪语音中的正弦噪声的技术。由于预测误差滤波器可以完全估计正弦噪声,因此在非语音段中输出变为零。在预测误差滤波器收敛后,停止对滤波器系数的更新。固定预测误差滤波器可以消除语音段中除语音信号外的正弦噪声。然而,该滤波器的频率特性依赖于其预测算法,并且系数可能收敛于导致语音退化的值。在本文中,我们提出了一种新的降噪算法,即一种泄漏LMS算法,使预测误差滤波器只去除正弦线谱而不产生语音退化
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sinusoidal Noise Reduction Method Using Leaky LMS Algorithm
A technique that uses a prediction error filter for reducing sinusoidal noises from a noisy speech has been proposed previously. Since the prediction error filter can estimate the sinusoidal noise completely, the output becomes zero in a non-speech segment. After the prediction error filter converges, the update of the filter coefficients is stopped. Then the fixed prediction error filter can cancel the sinusoidal noises except for a speech signal in a speech segment. However, frequency characteristics of the filter depend on its prediction algorithm, and the coefficients may converge the values which gives degradation of the speech. In this paper, we propose a new noise reduction algorithm which is a kind of leaky LMS algorithm, so that the prediction error filter removes only the sinusoidal line spectrum without speech degradation
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