Robust beamforming of microphone array using H infinity adaptive filtering technique

Abstract

In ASR (Automatic Speech Recognition) applications, one of the most important issues in the real-time beamforming of microphone arrays is the inability to capture the whole acoustic dynamics via a finite-length of data and a finite number of array elements. For example, the reflected source signal impinging from the side-lobe direction presents a coherent interference, and the non-minimal phase channel dynamics may require an infinite amount of data in order to achieve perfect equalization (or inversion). All these factors appear as uncertainties or un-modeled dynamics in the receiving signals. Traditional adaptive algorithms such as NLMS that do not consider these errors will result in performance deterioration. In this paper, a time domain beamformer using H-infinity filtering approach is proposed to adjust the beamforming parameters. Furthermore, this work also proposes a frequency domain approach called SPFDBB (Soft Penalty Frequency Domain Block Beamformer) using H-infinity filtering approach that can reduce computational efforts and provide a purified data to the ASR application. Experimental results show that the adaptive H-infinity filtering method is robust to the modeling errors and suppresses much more noise interference than that in the NLMS based method. Consequently, the correct rate of ASR is also enhanced.