%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