Literature DB >> 20674613

Learning grammatical categories from distributional cues: flexible frames for language acquisition.

Michelle C St Clair1, Padraic Monaghan, Morten H Christiansen.   

Abstract

Numerous distributional cues in the child's environment may potentially assist in language learning, but what cues are useful to the child and when are these cues utilised? We propose that the most useful source of distributional cue is a flexible frame surrounding the word, where the language learner integrates information from the preceding and the succeeding word for grammatical categorisation. In corpus analyses of child-directed speech together with computational models of category acquisition, we show that these flexible frames are computationally advantageous for language learning, as they benefit from the coverage of bigram information across a large proportion of the language environment as well as exploiting the enhanced accuracy of trigram information. Flexible frames are also consistent with the developmental trajectory of children's sensitivity to different sources of distributional information, and they are therefore a useful and usable information source for supporting the acquisition of grammatical categories. 2010 Elsevier B.V. All rights reserved.

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Year:  2010        PMID: 20674613     DOI: 10.1016/j.cognition.2010.05.012

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


  9 in total

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Authors:  Jessica Hall; Amanda Owen VAN Horne; Thomas Farmer
Journal:  J Child Lang       Date:  2017-11-10

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

Authors:  Jon A Willits; Mark S Seidenberg; Jenny R Saffran
Journal:  Cognition       Date:  2014-06-06

3.  Distributional Learning in College Students With Developmental Language Disorder.

Authors:  Jessica Hall; Amanda Owen Van Horne; Karla K McGregor; Thomas Farmer
Journal:  J Speech Lang Hear Res       Date:  2017-11-09       Impact factor: 2.297

4.  All together now: concurrent learning of multiple structures in an artificial language.

Authors:  Alexa R Romberg; Jenny R Saffran
Journal:  Cogn Sci       Date:  2013-06-14

5.  Word categorization from distributional information: frames confer more than the sum of their (Bigram) parts.

Authors:  Toben H Mintz; Felix Hao Wang; Jia Li
Journal:  Cogn Psychol       Date:  2014-08-27       Impact factor: 3.468

6.  Distributional learning of subcategories in an artificial grammar: Category generalization and subcategory restrictions.

Authors:  Patricia A Reeder; Elissa L Newport; Richard N Aslin
Journal:  J Mem Lang       Date:  2017-07-20       Impact factor: 3.059

7.  A universal cue for grammatical categories in the input to children: Frequent frames.

Authors:  Steven Moran; Damián E Blasi; Robert Schikowski; Aylin C Küntay; Barbara Pfeiler; Shanley Allen; Sabine Stoll
Journal:  Cognition       Date:  2018-03-16

8.  Mark my words: High frequency marker words impact early stages of language learning.

Authors:  Rebecca L A Frost; Padraic Monaghan; Morten H Christiansen
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2019-01-17       Impact factor: 3.051

9.  Lexical category acquisition is facilitated by uncertainty in distributional co-occurrences.

Authors:  Giovanni Cassani; Robert Grimm; Walter Daelemans; Steven Gillis
Journal:  PLoS One       Date:  2018-12-28       Impact factor: 3.240

  9 in total

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