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A lightweight backchannel head is introduced that predicts, from a full-duplex model's own hidden states, when a backchannel should begin, and once this probability crosses a tunable threshold, a backchannel is force-decoded.
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, finds end-of-turn recall stable across types, while interruption false positives are strongly type-dependent and concentrated in...
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