WorldSonus: Bringing Sound to Worlds
cs.SD, cs.AI, cs.CV, eess.AS
Submitted: 2026-10-06
Updated: 2026-10-06
Comments: 25 pages, 4 figures, 16 tables. Project page: https://noizai.github.io/WorldSonus/
Project page: https://noizai.github.io/WorldSonus
License: http://creativecommons.org/licenses/by-nc-sa/4.0/
The gist: Recent advances in world models have enabled increasingly realistic visual synthesis.
Abstract
Recent advances in world models have enabled increasingly realistic visual synthesis. However, these generated environments remain largely silent. Bringing sound to world models poses three core challenges: real-time generation to keep pace with interactive video streams, interactive control to respond to mid-stream sound instructions, and spatially aligned stereo to reflect scene geometry and camera motion. To address these demands, we introduce WorldSonus, an interactive video-to-audio framework designed for real-time spatial sound synthesis in world models. For real-time generation, WorldSonus employs a streaming causal autoregressive diffusion architecture that synthesizes audio chunks at a low real-time factor (RTF) of 0.41. For interactive control, we incorporate an audio-centric captioning pipeline with chunk-indexed prompt scheduling, enabling dynamic manipulation of sound events during generation. For spatial alignment, we leverage high-quality stereo supervision curated from diverse stereo and ambisonic data. Extensive experiments demonstrate that while tailored for world models, WorldSonus generalizes effectively to open-domain video-to-audio benchmarks, matching or outperforming state-of-the-art bidirectional models in both acoustic quality and spatial alignment. Project page: https://noizai.github.io/WorldSonus/
Sources
- LongCat-Video Technical Report
- A Short Note on the Kinetics-700 Human Action Dataset
- Visual Representation Matters: Exploiting Temporal Differences in Video-to-Audio Generation
- Omni2Sound: Towards Unified Video-Text-to-Audio Generation
- Ripple: Real-Time Streaming Audio-Video Generation With Cross-Modal Recurrent Memory
- AC-Foley: Reference-Audio-Guided Video-to-Audio Synthesis with Acoustic Transfer
- Infinite Worlds with Versatile Interactions
- Explorative Modeling: Unlocking a Third Pretraining Axis and End-to-End Generation
- LTX-Video: Realtime Video Latent Diffusion
- LTX-2: Efficient Joint Audio-Visual Foundation Model
- Matrix-game 2.0: An open-source, real-time, and streaming interactive world model
- Classifier-Free Diffusion Guidance
- StereoFoley: Object-Aware Stereo Audio Generation from Video
- Auto-Encoding Variational Bayes
- HunyuanVideo: A Systematic Framework For Large Video Generative Models
- Towards Streaming Synchronized Spatial Audio Generation via Autoregressive Diffusion Transformer
- PrismAudio: Decomposed Chain-of-Thoughts and Multi-dimensional Rewards for Video-to-Audio Generation
- SoundReactor: Frame-level Online Video-to-Audio Generation
- HunyuanVideo-Foley: Multimodal Diffusion with Representation Alignment for High-Fidelity Foley Audio Generation
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