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

arXiv 2509.13548 ↗First posted 16 Sep 2025cs.SD eess.AS stat.MLcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 16 references that are in the map. First posted on arXiv 16 Sep 2025.

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References · 3

  1. 2017Pyroomacoustics: A Python package for audio room simulations and array processing algorithmscited by 132
  2. 2024EARS: An Anechoic Fullband Speech Dataset Benchmarked for Speech Enhancement and Dereverberationcited by 64
  3. 2024Design and Analysis of Binaural Signal Matching with Arbitrary Microphone Arrays and Listener Head Rotationscited by 2

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  4. 2025BinauralFlow: A Causal and Streamable Approach for High-Quality Binaural Speech Synthesis with Flow Matching Models
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  6. 2025OWL: Geometry-Aware Spatial Reasoning for Audio Large Language Models
  7. 2026ImmersiveFlow: Stereo-to-7.1.4 spatial audio generation with flow matching
  8. 2026Physics-Aware Novel-View Acoustic Synthesis with Vision-Language Priors and 3D Acoustic Environment Modeling