Sector-Based Interference Cancellation for Robust Keyword Spotting Applications Using an Informed MPDR Beamformer

Abstract

A low-complexity, sector-based interference cancellation approach is proposed for voice-controlled devices, e.g., smart speakers. We propose an informed minimum power distortionless response beamformer that provides an optimal trade-off between noise reduction, dereverberation, and interference cancellation, with a minimal amount of target speaker distortions. Low complexity is achieved by using information on the target speaker in both the linear constraint and the beamformer’s minimization term, which allows sharing of the most complex beamformer computations across the different sectors. The results show that the proposed approach significantly improves keyword spotter performance compared to other approaches, such as the delay-and-sum beamformer, linearly constrained minimum variance beamformer, and traditional minimum power distortionless response beamformer.