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arXiv cs.AI· Pengjun Fang, Jingyi Fa, Kam Man Wu, Jiaming Wang, Haoyuan Huang, Yaguang Wu, Xiangjun Huang, Ziyang Ma, Weijia Chen, Hongyu Liu, Zeyue Tian, Qifeng Chen·· 10 天前AI 评分27

WorldSonus:为世界模型带来实时空间音效

WorldSonus: Bringing Sound to Worlds

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WorldSonus 是一个面向世界模型的交互式视频转音频框架,可实时合成空间音效,实时因子(RTF)低至 0.41。它采用流式因果自回归扩散架构,并通过以音频为中心的描述生成管线与分块索引提示词调度,支持生成过程中动态操控声音事件。该框架利用立体声与 ambisonic 数据监督实现空间对齐,在开放域视频转音频基准上匹配或超越当前最优的双向模型。

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Authors:Pengjun Fang, Jingyi Fa, Kam Man Wu, Jiaming Wang, Haoyuan Huang, Yaguang Wu, Xiangjun Huang, Ziyang Ma, Weijia Chen, Hongyu Liu, Zeyue Tian, Qifeng Chen

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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: this https URL
Comments: 25 pages, 4 figures, 16 tables. Project page: this https URL
Subjects: Sound (cs.SD); Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV); Audio and Speech Processing (eess.AS)
Cite as: arXiv:2610.08760 [cs.SD]
  (or arXiv:2610.08760v1 [cs.SD] for this version)
  https://doi.org/10.48550/arXiv.2610.08760

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Pengjun Fang [view email]
[v1] Tue, 6 Oct 2026 17:50:18 UTC (10,428 KB)

来源:arXiv cs.AI · arxiv.org