Publications

Abstract

Precision turn-taking may constitute a crucial part of the human endowment for communication. If so, it should be implemented similarly across language modalities, as in signed vs. spoken language. Here in the first experimental study of turn-end prediction in sign language, we find support for the idea that signed language, like spoken language, involves turn-type prediction and turn-end anticipation. In both cases, turns eliciting specific responses like questions accelerate anticipation. We also show remarkable cross-modality predictive capacity: non-signers anticipate sign turn-ends surprisingly well. Finally, we show that despite non-signers’ ability to intuitively predict signed turn-ends, early native signers do it much better by using their access to linguistic signals (here, question markers). As shown in prior work, question formation facilitates prediction, and age of sign language acquisition affects accuracy. The study thus sheds light on the kind of features that may facilitate turn-taking universally, and those that are language-specific.

Abstract

We investigate children’s online predictive processing as it occurs naturally, in conversation. We showed 1–7 year-olds short videos of improvised conversation between puppets, controlling for available linguistic information through phonetic manipulation. Even one- and two-year-old children made accurate and spontaneous predictions about when a turn-switch would occur: they gazed at the upcoming speaker before they heard a response begin. This predictive skill relies on both lexical and prosodic information together, and is not tied to either type of information alone. We suggest that children integrate prosodic, lexical, and visual information to effectively predict upcoming linguistic material in conversation.

Abstract

Conversational turns often proceed with very brief pauses between speakers. In order to maintain “no gap, no overlap” turntaking, we must be able to anticipate when an ongoing utterance will end, tracking the current speaker for upcoming points of potential floor exchange. The precise set of cues that listeners use for turn-end boundary anticipation is not yet established. We used an eyetracking paradigm to measure adults’ and children’s online turn processing as they watched videos of conversations in their native language (English) and a range of other languages they did not speak. Both adults and children anticipated speaker transitions effectively. In addition, we observed evidence of turn-boundary anticipation for questions even in languages that were unknown to participants, suggesting that listeners’ success in turn-end anticipation does not rely solely on lexical information.