RTF-steered binaural MVDR beamforming incorporating an external
microphone for dynamic acoustic scenarios
Nico GÖSSLING(1,2) , Simon DOCLO(1,2)(1) Signal Processing Group, Dept. of Medical Physics and Acoustics, University of Oldenburg, Germany(2) Cluster of Excellence Hearing4all, Germany

Abstract
Noise reduction algorithms for head-mounted assistive listening devices are crucial to improve speech intelligibility and speech quality in noisy environments. A well-known binaural noise reduction algorithm is the binaural
minimum variance distortionless response (BMVDR) beamformer [1, 2, 3], which can be steered using the relative transfer function (RTF) vectors of the target speaker. Aiming at improving the noise reduction performance,recently the usage of an additional external microphone has been explored. In this contribution, we consider the
recently proposed spatial coherence (SC) method to estimate the extended RTF vectors, assuming that the noise
component in the external microphone signal is uncorrelated with the noise component in the head-mounted
microphone signals [4, 5, 6]. Simulation results for a dynamic scenario with a moving speaker in a reverberantroom with diffuse noise show that the SC method yields a slightly better performance than the widely used covariance whitening method at a much lower computational complexity. Moreover, simulation results show that
the RTF-steered BMVDR beamformer filtering all microphone signals outperforms the RTF-steered BMVDR
beamformer filtering only the head-mounted microphone signals, a fixed BMVDR beamformer steered towards
the frontal direction as well as the external microphone signal.
Keywords: MVDR Beamforming, Binaural Noise Reduction, External MicrophoneACKNOWLEDGEMENTS
Funded by the Deutsche Forschungsgemeinschaft (DFG) – Projektnummer 352015383 – SFB 1330 B2 andProjektnummer 390895286 – EXC 2177/1.

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[6] N. Gößling, S. Doclo. RTF-steered binaural MVDR beamforming incorporating an external microphone fordynamic acoustic scenarios, in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, UK, May 2019, pp. 416-420.

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