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A Variable Step Size Algorithm for Speech Noise Reduction Method Based on Noise Reconstruction System

机译:一种基于噪声重构系统的语音降噪变步长算法

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摘要

We have proposed a noise reduction method based on a noise reconstruction system (NRS). The NRS uses a linear prediction error filter (LPEF) and a noise reconstruction filter (NRF) which estimates background noise by system identification. In case a fixed step size for updating tap coefficients of the NRF is used, it is difficult to reduce background noise while maintaining the high quality of enhanced speech. In order to solve the problem, a variable step size is proposed. It makes use of cross-correlation between an input signal and an enhanced speech signal. In a speech section, a variable step size becomes small so as not to estimate speech, on the other hand, large to track the background noise in a non-speech section.
机译:我们提出了一种基于噪声重建系统(NRS)的降噪方法。NRS 使用线性预测误差滤波器 (LPEF) 和噪声重建滤波器 (NRF),通过系统识别来估计背景噪声。如果使用固定的步长来更新 NRF 的抽头系数,则很难在降低背景噪音的同时保持增强语音的高质量。为了解决该问题,该文提出一种可变步长。它利用了输入信号和增强语音信号之间的互相关。在语音部分,可变步长变小,以便不估计语音,另一方面,变大步长以跟踪非语音部分中的背景噪声。

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