Considerable research indicates that learners are sensitive to probabilistic structure in
laboratory studies of artificial language learning. However, the artificial and simplified nature …

How do infants learn so rapidly and with little apparent effort? In 1996, Saffran, Aslin, and
Newport reported that 8‐month‐old human infants could learn the underlying temporal …

Memory is fleeting. New material rapidly obliterates previous material. How, then, can the
brain deal successfully with the continual deluge of linguistic input? We argue that, to deal …

While usage-based approaches to language development enjoy considerable support from
computational studies, there have been few attempts to answer a key computational …

The information that individuals can hold in working memory is quite limited, but researchers
have typically studied this capacity using simple objects or letter strings with no associations …

Spectacular progress in the information processing sciences (machine learning, wearable
sensors) promises to revolutionize the study of cognitive development. Here, we analyse the …

Numerous studies over the past decade support the claim that infants are equipped with
powerful statistical language learning mechanisms. The primary evidence for statistical …

We present an introduction to Bayesian inference as it is used in probabilistic models of
cognitive development. Our goal is to provide an intuitive and accessible guide to the what …

Statistical learning is a key concept in our understanding of language acquisition. Ample
work has highlighted its role in numerous linguistic functions—yet statistical learning is not a …

The term statistical learning in infancy research originally referred to sensitivity to transitional
probabilities. Subsequent research has demonstrated that statistical learning contributes to …