非平稳噪声环境下的语音增强算法

A More Effective Speech Enhancement Algorithm under Non-Stationary Noise Environment

文章针对非平稳噪声环境和低信噪比的情况,提出了一种基于低频区和高频区带噪语音特性的非平稳噪声估计,并结合人耳听觉掩蔽效应进行语音增强的算法。该算法首先通过非平稳噪声估计为加窗后的每一帧语音构造一个时变的权值实现对噪声的实时估计,然后结合人耳听觉特性计算出每一帧语音的不同Bark域的噪声掩蔽阈值,最后利用计算出的噪声掩蔽阈值自适应设定语音增强系数。仿真结果表明,该算法在抑制背景噪声,提高信噪比,减少语音失真等方面优于传统的语音增强方法。

Aiming at non-stationary noise environment and low SNR（signal to noise ratio）,we propose a more effective speech enhancement algorithm.The non-stationary noise estimation is based on noisy speech signal properties from low-frequency regions and high-frequency regions.Section 1 of the full paper explains what we believe to be a more effective algorithm;its core consists of：（1） we construct a time-varying weighting value for each frame of windowed speech signals through non-stationary noise estimation to realize the real time noise estimation;（2） utilizing the human auditory masking properties,we use Eq.（12） to calculate the masking threshold values of each frame of speech signals in its different BARK regions;（3） we then use the calculated masking threshold values to self-adaptively adjust the speech enhancement coefficients calculated by using Eq.（4）.Section 2 simulates our speech enhancement algorithm to verify its effectiveness;the simulation results,given in Figs.2 and 3 and Table 1,show preliminarily that our algorithm is more effective for reducing background noise,improving SNR and decreasing speech distortion.