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Abstract processing of syllabic structures in early infancy.
- Source :
-
Cognition [Cognition] 2024 Mar; Vol. 244, pp. 105663. Date of Electronic Publication: 2023 Dec 20. - Publication Year :
- 2024
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Abstract
- Syllables are one of the fundamental building blocks of early language acquisition. From birth onwards, infants preferentially segment, process and represent the speech into syllable-sized units, raising the question of what type of computations infants are able to perform on these perceptual units. Syllables are abstract units structured in a way that allows grouping phonemes into sequences. The goal of this research was to investigate 4-to-5-month-old infants' ability to encode the internal structure of syllables, at a target age when the language system is not yet specialized on the sounds and the phonotactics of native languages. We conducted two experiments in which infants were first familiarized to lists of syllables implementing either CVC (consonant-vowel-consonant) or CCV (consonant-consonant-vowel) structures, then presented with new syllables implementing both structures at test. Experiments differ in the degree of phonological similarity between the materials used at familiarization and test. Results show that infants were able to differentiate syllabic structures at test, even when test syllables were implemented by combinations of phonemes that infants did not hear before. Only infants familiarized with CVC syllables discriminated the structures at test, pointing to a processing advantage for CVC over CCV structures. This research shows that, in addition to preferentially processing the speech into syllable-sized units, during the first months of life, infants are also capable of performing fine-grained computations within such units.<br />Competing Interests: Declaration of Competing Interest None.<br /> (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1873-7838
- Volume :
- 244
- Database :
- MEDLINE
- Journal :
- Cognition
- Publication Type :
- Academic Journal
- Accession number :
- 38128322
- Full Text :
- https://doi.org/10.1016/j.cognition.2023.105663