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Research PaperResearchia:202610.07061

Coupled but Late: Turn-Taking Between Full-Duplex Speech Models in Unscripted Dialogue

Lichen Zhu

Abstract

Full-duplex speech models are trained to converse with a person, but they are increasingly made to converse with each other, in self-play data generation, agent societies, and model-based evaluation. In that loop no human absorbs a timing error: each model's turn-taking is the other's input. We ask what timing the loop settles into. Two PersonaPlex-7B instances exchange audio tokens on a shared clock in unscripted conversation, and one floor-transfer rule is applied to them and to Switchboard. T...

Submitted: October 7, 2026Subjects: AI; Artificial Intelligence

Description / Details

Full-duplex speech models are trained to converse with a person, but they are increasingly made to converse with each other, in self-play data generation, agent societies, and model-based evaluation. In that loop no human absorbs a timing error: each model's turn-taking is the other's input. We ask what timing the loop settles into. Two PersonaPlex-7B instances exchange audio tokens on a shared clock in unscripted conversation, and one floor-transfer rule is applied to them and to Switchboard. Their timing is coupled: re-pairing speakers across conversations destroys it. But the floor changes hands late, at a median of 400-560 ms against 137 ms for humans, and the last 120 ms of the partner's turn, where human projection places a tenth of its transfers, holds 1% of theirs. Delaying one direction of the channel shifts the response one-for-one and leaves the run-up to it empty, consistent with a reactive wait after the perceived end rather than the turn-end projection human timing requires.


Source: arXiv:2610.08683v1 - http://arxiv.org/abs/2610.08683v1 PDF: https://arxiv.org/pdf/2610.08683v1 Original Link: http://arxiv.org/abs/2610.08683v1

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Submission Info
Date:
Oct 7, 2026
Topic:
Artificial Intelligence
Area:
AI
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