Study On Methods For Speech Enhancement Based On Microphone Array In Complex Environment

Speech enhancement is one of the key technologies for the fields such as the information highway, multimedia, office automatization, modern communication, intelligent sytem and so on. The main aim of speech enhancement is to pick up speech information from the speech signals with noise, in order to obtain high quality speech. But due to the existence of the noise diversity and environment reverberation, the speech quality received by microphone is not so good, which affects the speech intelligibility and the speech processing performance. So effective noise suppression is necessary to improve the speech signals quality.Generally, single microphone speech enhancement has good noise suppression performance, but under complex acoustic environment, its noise supression performance declines rapidly. Microphone array technique combines the space and time information of speech signals, and has flexible beam control, higher space resolution, higher signal gain and better anti-interferenc performance. Now microphonw array technique becomes very important methods for capturing speaker speech and improving the speech quality in the intelligent communication system such as video conference system. In recent years, the speech enhancement methods based on microphone array have gradually become the research hot pot of speech processing.This thesis adopts microphone array processing and adaptive processing as the main signals processing tools, video conference system as the application background, this thesis studies some microphone array speech enhancement methods. Moreover, considering the delay estimation for microphone array speech enhancement, this thesis also discusses the time delay estimation under reverberation environment.The main research results of this thesis are as follows:(1) Research on adaptive beamforming and postfiltering beamforming combined microphone array speech enhancement methods. Considering the advantages of adaptive beamforming method and postfilter beamforming method under different noise fields, this thesis combines these two methods to propose a new beamforming speech enhancement method. The proposed method has good noise cancellation performance under both the correlative noise field and non-correlative noise filed. So it has good robust performance to the different noise.(2) Research on time delay estimation methods under reverberation environment. For the beamforming speech enhancement methods, it is normally to compensate the different channel speech signals with time delay. However, most of the time delay estimation algorithms don't take into account the reverberation influence. So this thesis proposes the time delay estimation method based on speech onset signals and generalized correlation weighting. This method first utilizes echo-avoidance (EA) reverberation model to pick up speech onset signals, then estimates the power spectrum with speech onset signals and carries out smooth processing, and at last adopts generalized correlation weighted method to estimate the time delay. This method can estimate the time delay accurately under reverberation environment. And the experiment result shows the validity of this method.(3) Research on the cepstrum based dereverberation methods. The speech dereverberation is also an important part of speech enhancement. This thesis proposes a microphone array speech enhancement. This method adopts an approximate method to gain the phase information from the noisy speech signals because the human ear is not sensitive to the speech phase. Compared wirh the traditional cepstrum speech enhancement methods, this method has less computational complex and can be used in the real video conference system which need to consider reverberation. Simulation shows the validity of this method.(4) Research on subspace methods for microphone array speech enhancement. In order to decrease the computational load, this thesis proposes the GSVD based microphone array speech enhancement method. This method is a suboptimal filtering speech enhancement, and it is not necessary to carry speech endpoint detection if the noise is white noise. Moreover, this thesis applies microphone array speech enhancement method to single microphone speech enhancement, and obtains good enhancement results. Simulation shows that the method can supress the noise effectively, and improve the signal to noise ratio.(5) Research on microphone array speech enhancement method based on the speeech production models. This thesis applies single microphone time-varying AR model speech enhancement methods to microphone array and combines the space characteristics of microphone array, then proposes the microphone array speech enhancement methods based on speech production models. This method can be paralell. In addition, this method uses less data points and AR model orders, and can realize real time speech enhancement. Simulation experiments show the validy of the method.