Non-adjacent dependency learning in infancy, and its link to language development

Rebecca L.A. Frost*, Andrew Jessop, Samantha Durrant, Michelle S. Peter, Amy Bidgood, Julian M. Pine, Caroline F. Rowland, Padraic Monaghan

*Corresponding author for this work

Research output: Contribution to journalArticle (journal)peer-review

22 Citations (Scopus)
49 Downloads (Pure)

Abstract

To acquire language, infants must learn how to identify words and linguistic structure in speech. Statistical learning has been suggested to assist both of these tasks. However, infants’ capacity to use statistics to discover words and structure together remains unclear. Further, it is not yet known how infants’ statistical learning ability relates to their language development. We trained 17-month-old infants on an artificial language comprising non-adjacent dependencies, and examined their looking times on tasks assessing sensitivity to words and structure using an eye-tracked head-turn-preference paradigm. We measured infants’ vocabulary size using a Communicative Development Inventory (CDI) concurrently and at 19, 21, 24, 25, 27, and 30 months to relate performance to language development. Infants could segment the words from speech, demonstrated by a significant difference in looking times to words versus part-words. Infants’ segmentation performance was significantly related to their vocabulary size (receptive and expressive) both currently, and over time (receptive until 24 months, expressive until 30 months), but was not related to the rate of vocabulary growth. The data also suggest infants may have developed sensitivity to generalised structure, indicating similar statistical learning mechanisms may contribute to the discovery of words and structure in speech, but this was not related to vocabulary size.

Original languageEnglish
Article number101291
Pages (from-to)1-19
JournalCognitive Psychology
Volume120
Early online date19 Mar 2020
DOIs
Publication statusPublished - 31 Aug 2020
Externally publishedYes

Keywords

  • Artificial grammar learning
  • Individual differences
  • Language acquisition
  • Speech segmentation
  • Statistical learning
  • Vocabulary development

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