An Advanced Expectation-Maximization Algorithm for Multimicrophone Speech Dereverberation and Noise Reduction

2nd International Symposium on Resource Exploration and Environmental Science

生态环境科学

Han, Liu^1 ; Ye, Zhongfu^1

School of Information Science and Technology, University of Science and Technology of China, Hefei

230026, China^1

关键词: Expectation-maximization algorithms;    Microphone signals;    Power spectral densities (PSD);    Reverberation time;    Room impulse response;    Spatial coherence;    Speech dereverberation;    Transform function;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/170/3/032108/pdf
DOI  :  10.1088/1755-1315/170/3/032108

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

In speech communication scenes, the microphone signals are often weakened by reverberation and ambient noise. Reverberation can be divided into an early part that is comprised of the direct speech and some early ones and a late part. In this paper, an advanced expectation-maximization (EM) algorithm for multimicrophone speech dereverberation and noise reduction, extending EM by taking the noise statistics into account, is proposed. This method aims at estimating the early parts filtered by early transform functions (ETFs). The EM algorithm is executed in two steps. In the E-step, the filtered early speech is calculated. Then, in the M-step, the ETFs, the power spectral density (PSD) of the filtered early speech and the late reverberation, and the spatial coherence matrix of the late reverberation are estimated. This algorithm is evaluated using an open-source room impulse responses (RIRs) database with a reverberation time of 0.36s and 0.61s under different signal-to-noise (SNR) conditions. It is proved an improvement compared with the original EM method.