Literature DB >> 24908342

Distributional structure in language: contributions to noun-verb difficulty differences in infant word recognition.

Jon A Willits1, Mark S Seidenberg2, Jenny R Saffran2.   

Abstract

What makes some words easy for infants to recognize, and other words difficult? We addressed this issue in the context of prior results suggesting that infants have difficulty recognizing verbs relative to nouns. In this work, we highlight the role played by the distributional contexts in which nouns and verbs occur. Distributional statistics predict that English nouns should generally be easier to recognize than verbs in fluent speech. However, there are situations in which distributional statistics provide similar support for verbs. The statistics for verbs that occur with the English morpheme -ing, for example, should facilitate verb recognition. In two experiments with 7.5- and 9.5-month-old infants, we tested the importance of distributional statistics for word recognition by varying the frequency of the contextual frames in which verbs occur. The results support the conclusion that distributional statistics are utilized by infant language learners and contribute to noun-verb differences in word recognition.
Copyright © 2014. Published by Elsevier B.V.

Entities:  

Keywords:  Language acquisition; Statistical learning; Verb learning; Word recognition

Mesh:

Year:  2014        PMID: 24908342      PMCID: PMC4107307          DOI: 10.1016/j.cognition.2014.05.004

Source DB:  PubMed          Journal:  Cognition        ISSN: 0010-0277


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