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Modeling the Development of Determiner Productivity in Children’s Early Speech
BibTeX
@MISC{Meylan_modelingthe,
author = {Stephan Meylan and Michael C. Frank and Roger Levy},
title = {Modeling the Development of Determiner Productivity in Children’s Early Speech},
year = {}
}
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Abstract
The English definite and indefinite articles (also known as de-terminers) are a useful index of early morphosyntactic pro-ductivity in children’s speech, and give evidence about chil-dren’s representation of syntactic abstractions. Previous work (i.e. Pine & Lieven, 1997) used a measure of productivity that shows a strong sensitivity to sample size and does not account for the relationship between adult input and children’s learn-ing. In this paper, we develop a more robust metric by em-ploying a hierarchical Bayesian model to characterize the de-gree of generalization implicit in observed determiner usage. By inferring parameters for a generative model over longitudi-nal corpora, we measure the trajectory of grammatical category abstraction. Our results are consistent with the hypothesis that child learners exhibit adult-like patterns of generalization quite early in the acquisition of determiners.
Keyphrases
early speech determiner productivity useful index generalization implicit syntactic abstraction child speech previous work adult input adult-like pattern english definite chil-dren representation grammatical category abstraction hierarchical bayesian model observed determiner usage generative model strong sensitivity pine lieven indefinite article early morphosyntactic pro-ductivity longitudi-nal corpus
