open access publication

Article, 2023

Caregiver linguistic alignment to autistic and typically developing children: A natural language processing approach illuminates the interactive components of language development

Cognition, ISSN 0010-0277, 1873-7838, Volume 236, Page 105422, 10.1016/j.cognition.2023.105422

Contributors

Fusaroli, Riccardo 0000-0003-4775-5219 (Corresponding author) [1] [2] Weed, Ethan 0000-0002-3921-9101 [2] Rocca, Roberta 0000-0001-9017-8088 [2] Fein, Deborah A [3] Naigles, Letitia R 0000-0003-2168-9700 [3]

Affiliations

  1. [1] University of Pennsylvania
  2. [NORA names: United States; America, North; OECD];
  3. [2] Aarhus University
  4. [NORA names: AU Aarhus University; University; Denmark; Europe, EU; Nordic; OECD];
  5. [3] University of Connecticut
  6. [NORA names: United States; America, North; OECD]

Abstract

BACKGROUND: Language development is a highly interactive activity. However, most research on linguistic environment has focused on the quantity and complexity of linguistic input to children, with current models showing that complexity facilitates language in both typically developing (TD) and autistic children. AIMS: After reviewing existing work on caregiver engagement of children's utterances, we aim to operationalize such engagement with automated measures of linguistic alignment, thereby providing scalable tools to assess caregivers' active reuse of their children's language. By assessing the presence of alignment, its sensitivity to the child's individual differences and how well it predicts language development beyond current models across the two groups, we showcase the usefulness of the approach and provide initial empirical foundations for further conceptual and empirical investigations. METHODS: We measure lexical, syntactic and semantic types of caregiver alignment in a longitudinal corpus involving 32 adult-autistic child and 35 adult-TD child dyads, with children between 2 and 5 years of age. We assess the extent to which caregivers repeat their children's words, syntax, and semantics, and whether these repetitions predict language development beyond more standard predictors. RESULTS: Caregivers tend to re-use their child's language in a way that is related to the child's individual, primarily linguistic, differences. Caregivers' alignment provides unique information improving our ability to predict future language development in both typical and autistic children. CONCLUSIONS: We provide evidence that language development also relies on interactive conversational processes, previously understudied. We share carefully detailed methods, and open-source scripts so as to systematically extend our approach to new contexts and languages.

Keywords

TD, active reuse, activity, age, alignment, approach, autistic children, automated measurement, caregiver engagement, caregivers, child dyads, child language, child's individuality, children, children's individual differences, children's utterances, children's word, complex, components of language development, context, conversion process, corpus, current models, development, differences, dyads, empirical foundation, empirical investigation, engagement, environment, evidence, foundations, group, individual differences, individuals, information, input, interacting components, interactive activities, investigation, language, language development, linguistic alignment, linguistic environment, linguistic input, longitudinal corpus, method, model, natural language processing approach, open-source scripts, predictors, presence, presence of alignment, process, processing approach, quantity, repetition, research, reuse, scripts, semantic types, semantics, sensitivity, standard predictors, syntax, unique information, use, utterances, words

Funders

  • National Institute on Deafness and Other Communication Disorders
  • Roche (United States)

Data Provider: Digital Science