双麦克风噪声消除的高斯混合模型法

为了解决基于相位差滤波器（PBF）双麦克风方法残留噪声较多的问题，本文在PBF方法基础上提出一种基于高斯混合模型的双麦克风噪声消除方法。该方法首先采用高斯混合模型（GMM）对目标语音存在(λ1)与目标语音不存(λ0)在这两种情况进行建模。其次，在实时增强阶段，根据贝叶斯分类器计算每帧的目标语音存在概率(TSPP)，随后根据噪声抑制最大化准则修正PBF的增益函数并得到改进的相位差滤波器（IPBF），最后将TSPP与 IPBF的增益函数相结合，进而得到一种用于双麦克风噪声消除的掩蔽滤波器。实验结果表明:本文提出算法可有效抑制残留噪声，尤其是在目标语音不存在的时间段 

Gaussian Mixture Model Method of Dual Microphone Noise Reduction

In order to reduce the residual noise caused by the method of phase-error based filter, a noise reduction approach based on dual microphones is proposed based on the Gaussian Mixture Model (GMM). First, two cases, i.e. target speech presence and target speech absence were modeled by the GMM, respectively. Then, the frame-based target speech present probability (TSPP) is calculated with the Bayesian classification. Next, an improved PBF (IPBF) is presented by modifying the gain function (GF) of PBF using the rule of noise suppression maximization. Finally, a mask filter for noise reduction is obtained by combining the GF of IPBF and TSPP. Some simulation results reveal that the proposed method could suppress the residual noise effectively, particularly in the period of target speech absence