Multi-microphone noise reduction and dereverberation techniques for speech applications

In typical speech communication applications, such as hands-free mobile telephony, voice-controlled systems and hearing aids, the recorded microphone signals are corrupted by background noise, room reverberation and far-end echo signals. This signal degradation can lead to total unintelligibility of the speech signal and decreases the performance of automatic speech recognition systems. In this thesis several multi-microphone noise reduction and dereverberation techniques are developed. In Part I we present a Generalised Singular Value Decomposition (GSVD) based optimal filtering technique for enhancing multi-microphone speech signals which are degraded by additive coloured noise. Several techniques are presented for reducing the computational complexity and we show that the GSVD-based optimal filtering technique can be integrated into a `Generalised Sidelobe Canceller’ type structure. Simulations show that the GSVD-based optimal filtering technique achieves a larger signal-to-noise ratio improvement than standard fixed and adaptive beamforming techniques and that it is more robust against several deviations from the assumed signal model. In Part II multi-microphone algorithms for time-delay estimation, dereverberation, and combined noise reduction and dereverberation are discussed. Since these algorithms require an estimate of the acoustic impulse responses, we also present batch and adaptive techniques for estimating the acoustic impulse responses, both in the time-domain and in the frequency-domain. We derive a stochastic gradient algorithm which iteratively estimates the generalised eigenvector corresponding to the smallest generalised eigenvalue and which can be used for time-delay estimation. We show that by integrating the normalised matched filter with the multi-channel Wiener filter, a combined noise reduction and dereverberation technique is obtained. In Part III several design procedures and cost functions are discussed for designing fixed broadband beamformers with an arbitrary desired spatial directivity pattern for a given arbitrary microphone array configuration, using an FIR filter-and-sum structure. We present two novel cost functions, which are based on eigenfilters. We discuss far-field, near-field and mixed near-field far-field broadband beamformer design, and we present two design procedures for designing broadband beamformers that are robust against gain and phase errors in the microphone characteristics.