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

Daylong at-home audio recordings from 10 Tseltal Mayan children (0;2–3;0; Southern Mexico) were analyzed for how often children engaged in verbal interaction with others and whether their speech environment changed with age, time of day, household size, and number of speakers present. Children were infrequently directly spoken to, with most directed speech coming from adults, and no increase with age. Most directed speech came in the mornings, and interactional peaks contained nearly four times the baseline rate of directed speech. Coarse indicators of children's language development (babbling, first words, first word combinations) suggest that Tseltal children manage to extract the linguistic information they need despite minimal directed speech. Multiple proposals for how they might do so are discussed.

Abstract

How do children learn to map linguistic forms onto their intended meanings? This chapter begins with an introduction to some theoretical and analytical tools used to study communicative acts. It then turns to communicative act development in spoken and signed language acquisition, including both the early scaffolding and production of communicative acts (both non-verbal and verbal) as well as their later links to linguistic development and Theory of Mind. The chapter wraps up by linking research on communicative act development to the acquisition of conversational skills, cross-linguistic and individual differences in communicative experience during development, and human evolution. Along the way, it also poses a few open questions for future research in this domain.

Abstract

Recent advances in large-scale data storage and processing offer unprecedented opportunities for behavioral scientists to collect and analyze naturalistic data, including from under-represented groups. Audio data, particularly real-world audio recordings, are of particular interest to behavioral scientists because they provide high-fidelity access to subtle aspects of daily life and social interactions. However, these methodological advances pose novel risks to research participants and communities. In this article, we outline the benefits and challenges associated with collecting, analyzing, and sharing multi-hour audio recording data. Guided by the principles of autonomy, privacy, beneficence, and justice, we propose a set of ethical guidelines for the use of longform audio recordings in behavioral research. This article is also accompanied by an Open Science Framework Ethics Repository that includes informed consent resources such as frequent participant concerns and sample consent forms.

Abstract

Children learn language from the speech in their home environment. Recent work shows that more infant-directed speech
(IDS) leads to stronger lexical development. But what makes IDS a particularly useful learning signal? Here, we expand on an attention-based account first proposed by Räsänen et al. (2018): that prosodic modifications make IDS less predictable, and thus more interesting. First, we reproduce the critical finding from Räsänen et al.: that lab-recorded IDS pitch is less predictable compared to adult-directed speech (ADS). Next, we show that this result generalizes to the home language environment, finding that IDS in daylong recordings is also less predictable than ADS but that this pattern is much less robust than for IDS recorded in the lab. These results link experimental work on attention and prosodic modifications of IDS to real-world language-learning environments, highlighting some challenges of scaling up analyses of IDS to larger datasets that better capture children’s actual input.

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.