TurnBench: A Multi-Domain Benchmark for Turn-Taking Dynamics in Spoken Dialogue

• URL: http://arxiv.org/abs/2608.25218v1
• Date: Tue, 25 Aug 2026 23:14:36 GMT
• Title: TurnBench: A Multi-Domain Benchmark for Turn-Taking Dynamics in Spoken Dialogue
• Abstract summary: Speakers in natural conversation take turns speaking and listening, deciding in real time when to take, hold, or yield the floor.<n>We present TurnBench, a benchmark that pairs a 30-hour, hand-labeled corpus of dyadic human conversation with a standardized evaluation protocol for end-of-turn and interruption detection.<n>We find end-of-turn recall stable across types, while interruption false positives are strongly type-dependent and concentrated in backchannel-dense interaction styles.
• Score: 79.83228182492354
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Speakers in natural conversation take turns speaking and listening, deciding in real time when to take, hold, or yield the floor. However, turn-taking evaluation remains limited due to the lack of a consistent, linguistically grounded evaluation protocol and hand-annotated data covering diverse conversation types. To address this, we present TurnBench, a multi-domain benchmark that pairs a 30-hour, hand-labeled corpus of dyadic human conversation with a standardized evaluation protocol for end-of-turn and interruption detection. We set conversation type as a controllable experimental variable, covering six distinct interaction styles, and triple-annotate each conversation. Benchmarking 14 heterogeneous turn-taking systems, we find end-of-turn recall stable across types, while interruption false positives are strongly type-dependent and concentrated in backchannel-dense interaction styles. Although in smooth floor transfers human listeners begin speaking a median 151 ms before the current turn ends, no current system performs equivalently without incurring excessive false positives. We release our corpus, a 104-hour training set, and a public leaderboard with an interactive dataset viewer at https://turnbench.sesame.com

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