Publications

Abstract

Language is a universal human ability, acquired readily by young children, whootherwise struggle with many basics of survival. And yet, language ability is variableacross individuals. Naturalistic and experimental observations suggest that children’slinguistic skills vary with factors like socioeconomic status and children’s gender.But which factors really influence children’s day-to-day language use? Here, weleverage speech technology in a big-data approach to report on a unique cross-culturaland diverse data set: >2,500 d-long, child-centered audio-recordings of 1,001 2- to48-mo-olds from 12 countries spanning six continents across urban, farmer-forager,and subsistence-farming contexts. As expected, age and language-relevant clinical risksand diagnoses predicted how much speech (and speech-like vocalization) childrenproduced. Critically, so too did adult talk in children’s environments: Children whoheard more talk from adults produced more speech. In contrast to previous conclusionsbased on more limited sampling methods and a different set of language proxies,socioeconomic status (operationalized as maternal education) was not significantlyassociated with children’s productions over the first 4 y of life, and neither weregender or multilingualism. These findings from large-scale naturalistic data advanceour understanding of which factors are robust predictors of variability in the speechbehaviors of young learners in a wide range of everyday contexts

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

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.