Title of article :
Distributional structure in language: Contributions to noun–verb difficulty differences in infant word recognition
Author/Authors :
Willits، نويسنده , , Jon A. and Seidenberg، نويسنده , , Mark S. and Saffran، نويسنده , , Jenny R.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2014
Pages :
8
From page :
429
To page :
436
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.
Keywords :
Word recognition , Language acquisition , Verb learning , Statistical Learning
Journal title :
Cognition
Serial Year :
2014
Journal title :
Cognition
Record number :
2078125
Link To Document :
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