A microphone array system for speech source localization, denoising, and dereverberation

There is a great deal of potential for advancement in distant-talker speech acquisition research, and a wealth of current and future technology depends upon these advances. The goal of this work is to allow users the opportunity to roam unfettered in diverse environments while still providing a high quality speech signal and a robustness to background noise and reverberation effects. In this thesis, a microphone array speech enhancement system is presented which has three main components: source localization, background noise reduction, and dereverberation. The localization algorithm is effective in the presence of both background noise and reverberations and simultaneously produces relative time delay estimates and a source location estimate. It provides a procedure applicable to all time delay estimators which either maximize or minimize an appropriate objective function, improving the estimators' robustness to environmental degradations. The denoising algorithm is a multi-microphone extension to the Minimum Statistics denoising technique [Martin (2001)]. This algorithm also has an additional and optional SNR-dependent beamforming stage that is shown to be very useful in certain environments. The final component is a multi-channel dereverberation algorithm which models the speech source and room reverberations independently. A weighting function is estimated and applied in the Wavelet Transform domain to de-emphasize portions which are less coherent across microphone signals, an indication of reverberation effects. Results for the various components are provided as proof of the effectiveness of the proposed multi-microphone speech enhancement system.

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