DiffuPlex: Accelerating Full-Duplex Spoken Dialog Models via Rolling Masked Diffusion

DiffuPlex is a rolling masked diffusion framework designed to accelerate full‑duplex spoken dialog models by predicting multiple future user and assistant frames in a single backbone pass. It consumes only a confident prefix of each predicted future while maintaining the original frame rate, and revises unplayed future content when the interaction diverges. Two inference policies—DiffuPlex‑LISTEN and DiffuPlex‑SPEAK—offer speedups of 1.46×–1.59× in deployment‑path wall‑clock time and 1.61×–1.80× in Core LM speed, with all backbone invocations completing within the 80 ms interaction interval, while preserving conversational quality and, in the LISTEN policy, speech naturalness.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

• diffusion