MOSS-TTSD: Text to Spoken Dialogue Generation
Spoken dialogue generation is crucial for applications like podcasts, dynamic commentary, and entertainment content, but poses significant challenges compared to single-utterance text-to-speech (TTS). Key requirements include accurate turn-taking, cross-turn acoustic consistency, and long-form stability, which current models often fail to address due to a lack of dialogue context modeling. To bridge this gap, we present MOSS-TTSD, a spoken dialogue synthesis model designed for expressive, multi-party conversational speech across multiple languages. With enhanced long-context modeling, MOSS-TTSD generates long-form spoken conversations from dialogue scripts with explicit speaker tags, supp...
| Authors | Yuqian Zhang, Donghua Yu, Zhengyuan Lin et al. |
|---|---|
| Primary category | cs.SD |
| Published | 20 March 2026 |
| Last updated at source | 20 March 2026 |
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