改进TF-GSC和改进后置滤波语音增强算法  

Improved TF-GSC and improved post filter speech enhancement algorithm

作　　者：杨诗童 杨飞[1] Yang Shitong;Yang Fei(School of Electrical Engineering and Automation,Wuhan University,Wuhan 430072,China)

机构地区：[1]武汉大学电气与自动化学院,武汉430072

出　　处：《电子测量技术》2023年第17期118-124,共7页Electronic Measurement Technology

摘　　要：由于声学环境中噪声的复杂性和不确定性,传统的多通道语音增强算法对于噪声的抑制效果不足,从而导致了较差的听觉体验。针对这一问题,提出了一种改进TF-GSC和改进后置滤波语音增强算法。算法使用最大似然法得到目标语音信号和噪声信号的功率谱密度,然后使用信号功率谱密度比值得到的变步长归一化最小均方算法来改进TF-GSC。还提出了联合信号功率谱密度比值和先验信噪比估计语音存在概率的改进最优修正对数幅度谱估计器。不同信噪比环境下的仿真实验表明,本文提出的算法可以有效地滤除相干噪声和非相干噪声,与其他算法相比,增强后的语音信号具有更高的信噪比和语音质量。Due to the complexity and uncertainty of noise in acoustic environment,the traditional multichannel speech enhancement algorithm has insufficient noise suppression effect,resulting in a poor auditory experience.To solve this problem,an improved TF-GSC and improved post filter speech enhancement algorithm was proposed in this paper.The algorithm used the maximum likelihood method to obtain the power spectral density of the target speech signal and noise signal,and then proposed an improved TF-GSC which used the variable step normalized least mean square algorithm obtained by the signal power spectral density ratio.An improved optimally modified log spectral spectrum estimator was also proposed using the estimated speech presence probability by combining the signal power spectral density ratio and a priori signal to noise ratio.The simulation experiments in different SNR environments show that the algorithm proposed in this paper can effectively filter coherent noise and incoherent noise.Compared with other algorithms,the enhanced speech signal has higher SNR and speech quality.

关 键 词：语音增强 传递函数广义旁瓣相消器 最优修正对数幅度谱估计器 最大似然 参数估计 

分 类 号：TN912.35[电子电信—通信与信息系统]