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arXiv · 2509.13548

Mixture-of-Experts Framework for Field-of-View Enhanced Signal-Dependent Binauralization of Moving Talkers

Manan Mittal·Thomas Deppisch·Joseph Forrer·Chris Le Sueur·Zamir Ben-Hur·David Lou Alon·Daniel D. E. Wong
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Abstract

We propose a novel mixture of experts framework for field-of-view enhancement in binaural signal matching. Our approach enables dynamic spatial audio rendering that adapts to continuous talker motion, allowing users to emphasize or suppress sounds from selected directions while preserving natural binaural cues. Unlike traditional methods that rely on explicit direction-of-arrival estimation or operate in the Ambisonics domain, our signal-dependent framework combines multiple binaural filters in an online manner using implicit localization. This allows for real-time tracking and enhancement of moving sound sources, supporting applications such as speech focus, noise reduction, and world-locked audio in augmented and virtual reality. The method is agnostic to array geometry offering a flexible solution for spatial audio capture and personalized playback in next-generation consumer audio devices.

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Manan Mittal, Thomas Deppisch, Joseph Forrer, Chris Le Sueur, Zamir Ben-Hur, David Lou Alon, Daniel D. E. Wong. 2025-09-16. Mixture-of-Experts Framework for Field-of-View Enhanced Signal-Dependent Binauralization of Moving Talkers. https://doi.org/10.1109/icassp55912.2026.11461442

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