Beamforming Through Online Convex Combination of Differential Beamformers

Abstract

Thanks to their high directivity, compact size, and reliable performance, differential microphone arrays (DMAs) have attracted great interest from both industry and academia as they have demonstrated great potential to be used in a wide range of applications for high-fidelity speech acquisition. Nevertheless, in many real-world applications, DMAs powered with fixed differential beamformers are often inadequate in suppressing interference, particularly in environments with multiple or moving sources. To address this issue, this work develops an adaptive convex combination (ACC)-based method, which combines multiple differential beamformers in an online manner for enhanced performance. While the major contribution is a new real-time processing algorithm that facilitates optimal linear combinations of different differential beamformers, making them adapted to dynamic environments, the presented method also provides valuable insights as how to combine different beamformers for online robust implementation.