QRD based MVDR beamforming for fast tracking of speech and noise dynamics

Beamforming techniques are becoming popular in a wide spectrum of applications thanks to their promising performance. We consider applying the minimum variance distortionless response (MVDR) beamformer in a dynamic scenario, where the desired speaker, the noise components or microphone array may move. The generalized sidelobe canceler (GSC) structure offers a convenient implementation of the MVDR, allowing to track the noise efficiently. Yet, noise reduction is degraded during speech tracking. We propose a QR Decomposition (QRD) based MVDR beamformer, which allows to track both speech and noise variations in dynamic scenarios without sacrificing noise reduction during speech segments. The proposed method utilizes the QRD algorithm for the implementation of a complete system required for the realization of an MVDR beamformer, which includes the identification of noisy speech or noise-only time-frequency bins, speech tracking and noise tracking. The proposed QRD based MVDR is efficiently implemented, and its overall computational complexity is O(M²), with M being the number of microphones. The advantages of the proposed method over the GSC are exemplified in a synthetically simulated scenario.