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arXiv · 2303.08967

Subspace Hybrid Beamforming for Head-worn Microphone Arrays

Sina Hafezi·Alastair H. Moore·Pierre Guiraud·Patrick A. Naylor·Jacob Donley·Vladimir Tourbabin·Thomas Lunner
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Abstract

A two-stage multi-channel speech enhancement method is proposed which consists of a novel adaptive beamformer, Hybrid Minimum Variance Distortionless Response (MVDR), Isotropic-MVDR (Iso), and a novel multi-channel spectral Principal Components Analysis (PCA) denoising. In the first stage, the Hybrid-MVDR performs multiple MVDRs using a dictionary of pre-defined noise field models and picks the minimum-power outcome, which benefits from the robustness of signal-independent beamforming and the performance of adaptive beamforming. In the second stage, the outcomes of Hybrid and Iso are jointly used in a two-channel PCA-based denoising to remove the 'musical noise' produced by Hybrid beamformer. On a dataset of real 'cocktail-party' recordings with head-worn array, the proposed method outperforms the baseline superdirective beamformer in noise suppression (fwSegSNR, SDR, SIR, SAR) and speech intelligibility (STOI) with similar speech quality (PESQ) improvement.

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Sina Hafezi, Alastair H. Moore, Pierre Guiraud, Patrick A. Naylor, Jacob Donley, Vladimir Tourbabin, Thomas Lunner. 2023-03-15. Subspace Hybrid Beamforming for Head-worn Microphone Arrays. https://arxiv.org/abs/2303.08967

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