Spherical harmonic domain noise reduction using an MVDR beamformer and DOA-based second-order statistics estimation

Most beamformers used for noise reduction rely on the accurate estimation of the second-order statistics of the noise, and in some cases, of the desired signal. Speech presence probability (SPP) based statistics estimators seek to update the estimates only when speech is absent/present, however, when used with a fixed a priori SPP, they cannot distinguish between a coherent desired source and coherent noise sources. We propose to distinguish between desired and noise sources by estimating the second-order statistics with a direction of arrival dependent a priori SPP, which we then use to compute the weights of a spherical harmonic domain minimum variance distortionless response filter.