改进的多级线性预测晚期混响抑制算法

在一个封闭的空间内，距离声源较远时接收到的语音信号通常会被混响所污染，其中晚期混响会在很大程度上降低语音可懂度。一般的去噪方法只能去除常见的加性噪声如白噪声，并不能去除房间冲激响应与干净语音卷积而成的混响，因此需要专门的去混响算法来去除晚期混响带来的影响。本文提出了一种新算法，在多级线性预测单通道去混响算法的基础上，修正了其预白化过程，改进后的算法可以提升语音前两个共振峰。实验结果证明，新算法在去除大部分混响的同时能够保留更多的有用语音的低频成分，因而提高了语音可懂度。 

Improved Late Reverberation Suppression Algorithm Using Multiple-step Linear Prediction

In an enclosure room, the speech signal captured by a distant microphone is usually contaminated by reverberation, in which the late reverberation severely degrades the speech intelligibility. Common denoising methods can only remove the additive noise such as white noise, not the reverberation which is the convolution of clean speech and room impulse response. Therefore, dereverberation algorithm should be applied to eliminate the bad effects caused by late reverberations. In this paper, we propose an improved dereverberation algorithm using multiple-step linear prediction. This method modifies the process of pre-whitening, which can raise the first two formants of the speech signal. Experimental results showed that new dereverberation algorithm can remove most of the late reverberations and reserve more low frequency components of clean speech, consequently improve the speech intelligibility.