基于Kalman滤波的GSC改进语音增强算法

Improved GSC Speech Enhancement Algorithm Based on Kalman Filtering

针对广义旁瓣相消器(Generalized sidelobe canceller,GSC)存在非相干噪声消除性能不佳的缺陷,提出了采用后置Kalman滤波器改进的GSC去噪算法。该算法通过归一化最小均方算法校正自适应噪声对消器,并将滤除方向性干扰噪声后的语音信号输出到Kalman滤波器中,对残余背景噪声进行迭代最小均方误差(Minimum mean square error,MMSE)估计,抑制非相干噪声与麦克风阵元所产生的热噪声。经过在不同信噪比条件下客观语音质量评估(Perceptual evaluation of speech quality,PESQ)及语谱图分析后证明,与传统的GSC以及后置谱减法的改进GSC相比,本算法在噪声消除上的表现更为优越,且增强后信号也更接近目标信号。

In view of the poor performance of generalized sidelobe canceller(GSC)of incoherent noise cancellation,an improved GSC denoising algorithm with post-Kalman filter is proposed.The algorithm corrects the adaptive noise canceller through the normalized least mean square algorithm,outputs the speech signal after filtering the directional interference noise to the Kalman filter,and iterates the residual background noise with the minimum mean square error(MMSE)to suppress incoherent noise and thermal noise generated by microphone array elements.After the objective speech quality evaluation,perceptual evaluation of speech quality(PESQ),and spectrogram analysis under different signal-to-noise ratio conditions,it is proved that compared with the traditional GSC and the improved GSC of postspectral subtraction,this algorithm is better at noise elimination.The performance is better,and the enhanced signal is closer to the target signal.