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PhysWave: Physics-Guided Latent Diffusion Models for Controllable Spatial Audio Generation

Paper recorded by Signals 4 on 2026-08-30 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-08-30 on arXiv · recorded by Signals 4 on 2026-09-01

Category: cs.AI · 人工智能 · first seen 2026-09-01

Abstract

Text-to-spatial audio generation, such as text-to-First-Order Ambisonics (FOA), provides a convenient way to create spatial audio for billion-dollar gaming and film industries. However, existing text-to-FOA methods are largely data-driven and may produce audio that violates acoustic relations between source direction and distance. They also separate descriptive and parametric control, forcing user

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#276 most recent of 300 cs.AI papers we have recorded · ↑ newer: HoopMind: A Real-Time Neural Game-Tree System for Opponent-Aware Posse · ↓ older: Evaluating LLMs on Conversational Text-to-SQL under Chain Ambiguity an
Cite this page: PhysWave: Physics-Guided Latent Diffusion Models for Controllable Spatial Audio Generation: the #276 most recent of 300 cs.AI papers we have recorded (as of 2026-08-30). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/physwave-physics-guided-latent-diffusion-models-for-controllable-spatial-audio-g.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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