Gammatone滤波器修正的多级线性预测去混响

Dereverberation Using Multiple-step Linear Prediction Modified with Gammatone Filter Bank

在相对封闭的空间内,使用一些通讯设备时,距离声源较远的麦克风接收到的语音信号通常会被混响和噪声所污染,这些干扰信号会在很大程度上降低语音可懂度。带噪的混响语音经过去混响和消噪算法处理后,常常会残留一些音乐噪声,使得人耳听起来很不舒服。本文根据人耳对不同频带的听觉特征,引入Gammatone听觉滤波器组,提出了Gammatone滤波器修正的多级线性预测去混响算法。实验结果证明,新算法有效的解决了去混响及消噪后的残留音乐噪声问题,提高了语音的清晰度和舒适度。

When people use communication equipment in an enclosure room, the speech signal captured by a distant microphone is usually contaminated by reverberation and noise, which will severely degrades the speech intelligibility. After the noisy reverberant speech signal is processed with denoise and dereverberation algorithms, residual ＂musical noise＂ has a great effect on the speech intelligibility and auditory comfort level. In this paper, we introduced Gammatone filter banks which were designed to simulate the human basilar membrane response to sound input, and used them to smooth and modify the gain function obtained by spectral subtraction method. Experimental results showed that the new algorithm suppressed the ＂musical noise＂ efficiently and consequently improved the speech intelligibility and auditory comfort level.