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

• URL: http://arxiv.org/abs/2509.13548v2
• Date: Thu, 18 Sep 2025 01:20:59 GMT
• Title: Mixture-of-Experts Framework for Field-of-View Enhanced Signal-Dependent Binauralization of Moving Talkers
• Authors: Manan Mittal, Thomas Deppisch, Joseph Forrer, Chris Le Sueur, Zamir Ben-Hur, David Lou Along, Daniel D. E. Wong,
• Abstract summary: We propose a novel mixture of experts framework for field-of-view enhancement in signal matching.<n>Our approach enables dynamic spatial audio rendering that adapts to continuous talker motion, allowing users to emphasize or suppress sounds from selected directions.<n>This allows for realtime tracking and enhancement of moving sound sources, supporting applications such as speech focus, noise reduction, and world-locked audio in augmented and virtual reality.
• Score: 2.614081506519191
• License: http://creativecommons.org/licenses/by/4.0/
• 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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