Speech Enhancement And DOA Estimate Research Based On Microphone Array

Microphone array based speech enhancement has wide applications. However, a big array aperture may greatly limit its applications, such as telephone and some other Embedded device. The research for small microphone array based speech enhancement has great value.In this thesis, some algorithms and methods for small microphone array based speech enhancement are proposed first. Then two main algorithms that synthesize the proposed algorithms and methods are presented.Firstly, the Crosstalk Resistant Adaptive Noise Cancellation algorithm is proposed. The algorithm employs only two adaptive filters. It has good stability and low computational complexity. Secondly, three combined algorithms of CRANC with other existing algorithms are presented. One combined algorithm is the cascade of CRANC with improved spectrum subtraction. The second is the combination with delay and sum beamforming, and the third is the combination with Weiner post-filtering. These combined algorithms may achieve better results than any one algorithm alone. Thirdly, improvement are made for CRANC itself. One is to improve CRANC with multichannel distorted signals filtering for its second-stage filter. The other is to add fixed beamforming. Finally, two improved GSC algorithms based on crosstalk resistant adaptive signal cancellation(CRASC) are proposed. One is to use every channel of the array signal as the main channel signal and others as the referential signals for an ACRASC to get the noise estimations. The other is to obtain the noise estimations by establishing a shared distorted speech signal. It is proved that the essence of the two proposed improved GSC algorithms is to extend the common blocking matrix to a time-variable vector blocking matrix. A combination with TDOA and RANC method has also been discussed, It also achieve a better result.