Coupled but Late: Turn-Taking Between Full-Duplex Speech Models in Unscripted Dialogue
cs.AI
Submitted: 2026-10-06
Updated: 2026-10-06
Comments: The paper is under review
License: http://creativecommons.org/licenses/by-nc-sa/4.0/
The gist: 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.
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. 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.
Sources
- Moshi: a speech-text foundation model for real-time dialogue
- PersonaPlex: Voice and Role Control for Full Duplex Conversational Speech Models
- DuplexGen: Adaptive Synthesis of Human-AI Turn-Taking Dialogues
- Synchronization and Turn-Taking in Full-Duplex Speech Dialogue Models
- Overcoming State Inertia in Full-Duplex Spoken Language Models via Activation Steering
- Instruct-FD: Can Your Full-Duplex Speech System Follow Turn-Taking Instructions?
- Multi-Faceted Interactivity Alignment in Full-Duplex Speech Models
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