The real-time implementation of the existing multi-channel Wiener filter (MWF) algorithms suffer from performance degradation due to the lack of robustness against estimation errors of the second-order statistics. The reasons are twofold: one, the estimation of the statistics relies on real voice activity detector (VAD), which often fails in adverse environments. Second, the MWF solutions involve estimation of the second order clean speech statistics, which also exaggerates the errors. This paper presents an MWF algorithm that requires neither VAD nor clean speech statistics. Performance evaluation under real scenarios shows that the proposed method outperforms the conventional MWF solution in terms of the trade-off between noise reduction and speech distortion.

In broadband beamformer applications with dynamically moving sources, it can be important to have a simple mechanism to steer the main-beam. It can also be desirable if the beampattern of the beamformer is invariant to the look direction. A number of design methods for such beamformers, based on the spherical harmonic transform, have been reported in the literature. However, these methods require the sensor positions to satisfy a certain condition which may conflict with practical considerations. This paper proposes a design method which obviates this restriction thus allowing for spherical arrays with arbitrary sensor configurations. Moreover, for a comparable level of performance and computational complexity to the existing spherical harmonic beamformers, the proposed beamformer requires fewer sensors. The trade-off is that the design of the beamformer now depends on the sensor positions. Other considerations, such as the effects of array mis-orientation and robustness, are also discussed in this paper and illustrated by design examples.

Beamformers are known to be sensitive to errors and mismatches in their array elements. This paper proposes a robust steerable broad band beamformer design using the Farrow structure and for arbitrary array geometry. The design formulation includes stochastic models describing the microphone characteristics as random variables, thus allowing flexibility for microphone errors. This method establishes a direct relationship in controlling the robustness specification in the design from given microphone characteristics. The robust design procedure optimises the mean performance of the beamformer. Design examples show significant reduction in error sensitivity in the robust design formulation.