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arXiv · 2609.29418

Controlling Backchannels in Streamable Full-duplex Models

Maike Züfle·Peter Polák·Sefik Emre Eskimez·Jan Niehues·Peter Bell·Ondřej Klejch
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Abstract

Backchannels, brief acknowledgements like "uh-huh" produced while the other party may still be talking, are central to natural conversation, but full-duplex spoken dialogue models rarely model them explicitly. We introduce a lightweight backchannel head that predicts, from a full-duplex model's own hidden states, when a backchannel should begin. Once this probability crosses a tunable threshold, a backchannel is force-decoded. Attached to both a 7B (PersonaPlex) and a 1B (F-Actor) model, it generalizes across scale. Probing confirms the hidden states anticipate real human timing, and generation evaluation shows more frequent, better-timed backchannels. Human raters judge the resulting backchannels on par with real ones.

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Maike Züfle, Peter Polák, Sefik Emre Eskimez, Jan Niehues, Peter Bell, Ondřej Klejch. 2026-09-24. Controlling Backchannels in Streamable Full-duplex Models. https://arxiv.org/abs/2609.29418

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