Modeling Child Divergences from Adult Grammar

Sam Sahakian, Benjamin Snyder


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.
Anthology ID:
Q13-1011
Volume:
Transactions of the Association for Computational Linguistics, Volume 1
Month:
Year:
2013
Address:
Cambridge, MA
Editors:
Dekang Lin, Michael Collins
Venue:
TACL
SIG:
Publisher:
MIT Press
Note:
Pages:
125–138
Language:
URL:
https://aclanthology.org/Q13-1011
DOI:
10.1162/tacl_a_00215
Bibkey:
Cite (ACL):
Sam Sahakian and Benjamin Snyder. 2013. Modeling Child Divergences from Adult Grammar. Transactions of the Association for Computational Linguistics, 1:125–138.
Cite (Informal):
Modeling Child Divergences from Adult Grammar (Sahakian & Snyder, TACL 2013)
Copy Citation:
PDF:
https://aclanthology.org/Q13-1011.pdf