Using Semantic Uncertainty to Estimate Transition Relevance in Turn-taking

A new arXiv paper (2609.10934v1) reports that modeling semantic uncertainty — an LLM-derived measure of how strongly a turn so far constrains what may plausibly come next — substantially outperforms prompt-based and fine-tuned text-only baselines at identifying Transition Relevance Places (TRPs) in unscripted spoken dialogue. The authors sampled possible continuations of ongoing turns and used changes in semantic dispersion to locate TRPs, evaluating the approach on a dataset with TRP labels derived from real-time listener responses rather than retrospective annotation. The results provide empirical support for the view that evolving semantic constraints inform perceived turn-taking opportunities, addressing a central challenge for Spoken Dialogue Systems that produce ill-timed responses in unscripted interaction.

arXiv:2609.10934v1 Announce Type: new Abstract: Turn-taking is a fundamental mechanism that governs when interlocutors speak and listen. Although Spoken Dialogue Systems SDS exploit a range of linguistic, acoustic, and non-verbal cues, they produce ill-timed responses in unscripted interaction. A central challenge is anticipating Transition Relevance Places TRPs , or opportunities, not obligations, for a listener to take the floor. Human listeners do not wait for turn endings; as an utterance unfolds, they use expectations about its developing meaning to anticipate TRPs and decide whether to take the floor. We examine whether these evolving expectations can be modeled through semantic uncertainty -- an LLM-derived measure of how strongly a turn so far constrains what may plausibly come next. To do so, we sample possible continuations of an ongoing turn and use changes in semantic dispersion to identify TRPs within turns. We evaluate this account on a dataset with TRP labels derived from real-time listener responses, rather than retrospective annotation. Our approach substantially outperforms prompt-based and fine-tuned text-only baselines, providing empirical support for the view that evolving semantic constraints inform perceived turn-taking opportunities in unscripted interaction.