SIREN: Spatially-Informed Reconstruction of Binaural Audio with Vision

Mingyeong Song; Seoyeon Ko; Junhyug Noh

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arXiv · 2603.29820

SIREN: Spatially-Informed Reconstruction of Binaural Audio with Vision

Mingyeong Song·Seoyeon Ko·Junhyug Noh

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Abstract

Binaural audio delivers spatial cues essential for immersion, yet most consumer videos are monaural due to capture constraints. We introduce SIREN, a visually guided mono to binaural framework that explicitly predicts left and right channels. A ViT-based encoder learns dual-head self-attention to produce a shared scene map and end-to-end L/R attention, replacing hand-crafted masks. A soft, annealed spatial prior gently biases early L/R grounding, and a two-stage, confidence-weighted waveform-domain fusion (guided by mono reconstruction and interaural phase consistency) suppresses crosstalk when aggregating multi-crop and overlapping windows. Evaluated on FAIR-Play and MUSIC-Stereo, SIREN yields consistent gains on time-frequency and phase-sensitive metrics with competitive SNR. The design is modular and generic, requires no task-specific annotations, and integrates with standard audio-visual pipelines.

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Mingyeong Song, Seoyeon Ko, Junhyug Noh. 2026-03-31. SIREN: Spatially-Informed Reconstruction of Binaural Audio with Vision. https://arxiv.org/abs/2603.29820

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