@article{sahakian-snyder-2013-modeling,
    title = "Modeling Child Divergences from Adult Grammar",
    author = "Sahakian, Sam  and
      Snyder, Benjamin",
    editor = "Lin, Dekang  and
      Collins, Michael",
    journal = "Transactions of the Association for Computational Linguistics",
    volume = "1",
    year = "2013",
    address = "Cambridge, MA",
    publisher = "MIT Press",
    url = "https://aclanthology.org/Q13-1011/",
    doi = "10.1162/tacl_a_00215",
    pages = "125--138",
    abstract = "During the course of first language acquisition, children produce linguistic forms that do not conform to adult grammar. In this paper, we introduce a data set and approach for systematically modeling this child-adult grammar divergence. Our corpus consists of child sentences with corrected adult forms. We bridge the gap between these forms with a discriminatively reranked noisy channel model that translates child sentences into equivalent adult utterances. Our method outperforms MT and ESL baselines, reducing child error by 20{\%}. Our model allows us to chart specific aspects of grammar development in longitudinal studies of children, and investigate the hypothesis that children share a common developmental path in language acquisition."
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    <abstract>During the course of first language acquisition, children produce linguistic forms that do not conform to adult grammar. In this paper, we introduce a data set and approach for systematically modeling this child-adult grammar divergence. Our corpus consists of child sentences with corrected adult forms. We bridge the gap between these forms with a discriminatively reranked noisy channel model that translates child sentences into equivalent adult utterances. Our method outperforms MT and ESL baselines, reducing child error by 20%. Our model allows us to chart specific aspects of grammar development in longitudinal studies of children, and investigate the hypothesis that children share a common developmental path in language acquisition.</abstract>
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%0 Journal Article
%T Modeling Child Divergences from Adult Grammar
%A Sahakian, Sam
%A Snyder, Benjamin
%J Transactions of the Association for Computational Linguistics
%D 2013
%V 1
%I MIT Press
%C Cambridge, MA
%F sahakian-snyder-2013-modeling
%X During the course of first language acquisition, children produce linguistic forms that do not conform to adult grammar. In this paper, we introduce a data set and approach for systematically modeling this child-adult grammar divergence. Our corpus consists of child sentences with corrected adult forms. We bridge the gap between these forms with a discriminatively reranked noisy channel model that translates child sentences into equivalent adult utterances. Our method outperforms MT and ESL baselines, reducing child error by 20%. Our model allows us to chart specific aspects of grammar development in longitudinal studies of children, and investigate the hypothesis that children share a common developmental path in language acquisition.
%R 10.1162/tacl_a_00215
%U https://aclanthology.org/Q13-1011/
%U https://doi.org/10.1162/tacl_a_00215
%P 125-138
Markdown (Informal)
[Modeling Child Divergences from Adult Grammar](https://aclanthology.org/Q13-1011/) (Sahakian & Snyder, TACL 2013)
ACL