Infant statistical-learning ability is related to real-time language processing

Author: Lany, J.; Shoaib, A.; Thompson, A.; Estes, K.G.

Description: Infants are adept at learning statistical regularities in artificial language materials, suggesting that the ability to learn statistical structure may support language development. Indeed, infants who perform better on statistical learning tasks tend to be more advanced in parental reports of infants’ language skills. Work with adults suggests that one way statistical learning ability affects language proficiency is by facilitating real-time language processing. Here we tested whether 15-month-olds’ ability to learn sequential statistical structure in artificial language materials is related to their ability to encode and interpret native-language speech. Specifically, we tested their ability to learn sequential structure among syllables (Experiment 1) and words (Experiment 2), as well as their ability to encode familiar English words in sentences. The results suggest that infants’ ability to learn sequential structure among syllables is related to their lexical-processing efficiency, providing continuity with findings from children and adults, though effects were modest.

Subject Headings: Infant; Statistical-learning ability; Language processing; Real-time

Keywords: Infant statistical-learning ability is related to real-time language processing

Publication year: 2018

Journal or book title: Journal of Child Language

Volume: 45

Issue: 2

Pages: 368-391

Find the full text : https://www.cambridge.org/core/journals/journal-of-child-language/article/infant-statisticallearning-ability-is-related-to-realtime-language-processing/D127D3D906807338A006A2A1D915C200

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Type: Journal Article

Serial number: 2439