Neural network models have recently made striking progress in natural language processing, but they are typically trained on orders of magnitude more language input than children receive. What can these neural networks, which are primarily distributional learners, learn from a naturalistic subset of a single child's experience? We examine this…

It has been suggested that external and/or internal limitations paradoxically may lead to superior learning, that is, the concepts of "starting small" and "less is more" (Elman, 1993; Newport, 1990). In this paper, we explore the type of incremental ordering during training that might help learning, and what mechanism explains…

Strong correlations between vocabulary and grammar are well attested in language development in monolingual and bilingual children. What is less clear is whether there is any directionality in the relationship between the two constructs, whether it is predictive over time, and the extent to which it is affected by language input. In the present…

Becoming productive with grammatical categories is a gradual process in children's language development. Here, we investigated this transition process by focusing on Turkish causatives. Previous research examining spontaneous and elicited production of Turkish causatives with familiar verbs attested the onset and early stages of productivity at…

Children with developmental language disorder (DLD) have significant deficits in language ability that cannot be attributed to neurological damage, hearing impairment, or intellectual disability. The symptoms displayed by children with DLD differ across languages. In English, DLD is often marked by severe difficulties acquiring verb inflection.…

Language learning requires linguistic input, but several studies have found that knowledge of second language (L2) rules does not seem to improve with more language exposure (e.g., Johnson & Newport, 1989). One reason for this is that previous studies did not factor out variation due to the different rules tested. To examine this issue, we…

We introduce a set of biologically and computationally motivated design choices for modeling the learning of language, or of other types of sequential, hierarchically structured experience and behavior, and describe an implemented system that conforms to these choices and is capable of unsupervised learning from raw natural-language corpora. Given…