Research suggests that second language words are learned faster when they are similar in phonological structure or accent to the words of an individual's first language. Many major theories suggest this happens because of differences in frequency of exposure and context between first and second language words. Here, we examine the independent…

We evaluate here the performance of four models of cross-situational word learning: two global models, which extract and retain multiple referential alternatives from each word occurrence; and two local models, which extract just a single referent from each occurrence. One of these local models, dubbed "Pursuit," uses an associative…

Humans are remarkably sensitive to the statistical structure of language. However, different mechanisms have been proposed to account for such statistical sensitivities. The present study compared adult learning of syntax and the ability of two models of statistical learning to simulate human performance: Simple Recurrent Networks, which learn by…

We present a neurocomputational model with self-organizing maps that accounts for the emergence of taxonomic responding and fast mapping in early word learning, as well as a rapid increase in the rate of acquisition of words observed in late infancy. The quality and efficiency of generalization of word-object associations is directly related to…

Argues that much of language acquisition is sequence learning and that the resultant long-term knowledge base of language sequences serves as the database for grammar acquisition. The article also proposes mechanisms to analyze sequence information that result in knowledge of underlying grammar. (184 references) (Author/CK)