Reference-Driven Multi-Speaker Audio Scene Generation from In-the-Wild Priors
Existing multi-speaker dialogue systems bind speakers to utterances through structured supervision: per-turn tags, multi-stream transcriptions, or learnable speaker embeddings. These systems operate within speech-only pipelines that produce clean vocal sequences without the ambient texture of real conversations. We take a different approach. Our method, ScenA, conditions a text-to-audio flow-matching foundation model, pretrained on large-scale in-the-wild data, directly on multiple reference voices and a free-form natural language prompt that describes an entire multi-speaker audio scene. Leveraging such a foundational model allows us to inherit its capacity for natural, non-studio audio:...
| Authors | Michael Finkelson, Daniel Segal, Eitan Richardson et al. |
|---|---|
| Primary category | cs.SD |
| Published | 17 June 2026 |
| Last updated at source | 17 June 2026 |
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