DevLex: a self-organizing neural network model of the development of lexicon

In this paper we present the DevLex model of language acquisition. DevLex consists of two self-organizing maps (a growing semantic map and a phonological map) that are connected via associative links. It simulates the early stages of lexical development in children, in particular, word confusion as evidenced in naming errors. The simulation results indicate that the rate of word confusion is modulated by developmental profile of vocabulary increase, word density of competing neighbors, and rate of lexical growth. These results match up with hypotheses from empirical research on lexical development.