MoSAT: Human Motion Generation from Spatial Audio and Textual Description
Human motion is shaped by both external acoustic events and behavioral intent: spatial audio conveys environmental cues that elicit or guide a response, while text specifies the desired action and how it should be performed. In this paper, we study the novel task of human motion synthesis jointly conditioned on spatial audio and natural language, a problem that has been largely overlooked in previous research. To support this task, We introduce STAM, a dataset of motion sequences paired with spatial audio and detailed textual annotations whose rich vocabulary affords precise and nuanced specification of human motions. We further introduce MoSAT, a latent flow-matching framework for full-b...
| Authors | Shuyang Xu, Zhiyang Dou, Yiduo Hao et al. |
|---|---|
| Primary category | cs.GR |
| Published | 20 September 2026 |
| Last updated at source | 20 September 2026 |
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