Papers by Zengwei Yao

1 papers
ZipVoice-Dialog: Non-Autoregressive Spoken Dialogue Generation with Flow Matching (2026.findings-acl)

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Challenge: Existing autoregressive models for dialogue generation suffer from high latency and stability issues.
Approach: They propose a non-autoregressive (NAR) zero-shot spoken dialogue generation model based on flow-matching.
Outcome: The proposed model outperforms existing models in speech generation due to poor speech intelligibility and turn-taking precision.

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