DiffuPlex: Accelerating Full-Duplex Spoken Dialog Models via Rolling Masked Diffusion
Recent full-duplex spoken dialog models enable simultaneous listening and speaking, but fine-grained models still advance their backbone autoregressively at every interaction frame. We introduce DiffuPlex, a rolling masked diffusion framework that reduces this sequential computation by predicting multiple future user and assistant frames in a single backbone wake. DiffuPlex consumes only a confident prefix of each predicted future while interaction continues at the original frame rate. As user speech arrives, it checks the corresponding user predictions and, when the interaction diverges, preserves already played assistant content while revising only the unplayed future. We consider two i...
| Authors | Heeseung Kim |
|---|---|
| Primary category | cs.SD |
| Published | 8 October 2026 |
| Last updated at source | 8 October 2026 |
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