最大输出信噪比(Signal-to-noise ratio,SNR)准则下,广义特征值(Generalized eigenvalue,GEV)波束形成存在复系数难以控制的问题,在复杂的声学环境中容易导致输出信号严重失真.针对复系数估计问题,本文提出一种基于最小均方误差(Minimum mean square error,MMSE)的复系数估计方法,并通过引入语音失真权重因子(Speech distortion weight,SDW),调节降噪效果和语音失真之间的权重关系,进而提出了基于SDW-MMSE的广义特征值稳健波束形成方法.通过最大似然法估计目标信号和噪音信号的功率谱,进而求解主广义特征向量.进一步基于SDW-MMSE估计复系数,将复系数与主广义特征向量相结合,从而得到基于SDW-MMSE的广义特征值稳健波束形成滤波向量.仿真实验结果表明,本文提出的波束形成方法可有效消除相干噪声和非相干噪声,具有输出信噪比高、语音失真少等稳健性能.
Generalized Eigenvalue Robust Beamforming Based on SDW-MMSE
Under the criterion of maximum output signal-to-noise ratio(SNR),the problem of difficult control of complex-valued coefficients in generalized eigenvalue(GEV)beamforming is encountered,and severe distortion of the output signal can be caused in complex acoustic environments.To address the issue of complex-valued coefficient estimation,a complex-valued coefficient estimation method based on minimum mean square error(MMSE)is proposed in this paper.By introducing a speech distortion weight factor(SDW),the weight relationship between noise reduction and speech distortion is adjusted,thereby proposing a method for generalized eigenvalue robust beamforming based on SDW-MMSE.The power spectra of the target and noise signals are estimated using maximum likelihood method,and the main generalized eigenvectors are then determined.Furthermore,the complex-valued coefficients are estimated,and the complex coefficients are combined with the principal generalized eigenvector to obtain the generalized eigenvalue robust beamforming filter vector based on SDW-MMSE.Through simulation experiments,it is demonstrated that the proposed beamforming method effectively eliminates coherent and incoherent noise,and exhibits robust performance with high output SNR and low speech distortion.
万方数据
维普
