Bilingual lexical interactions in an unsupervised neural network model

In this paper we present an unsupervised neural network model of bilingual lexical development and interaction. We focus on how the representational structures of the bilingual lexicons can emerge, develop, and interact with each other as a function of the learning history. The results show that: (1) distinct representations for the two lexicons can develop in our network when the two languages are learned simultaneously; (2) the representational structure is highly dependent on the onset time of the second language (L2) learning if the two languages are learned sequentially; and (3) L2 representation becomes parasitic on the representation of the first language when the learning of L2 occurs late. The results suggest a dynamic developmental picture for bilingual lexical acquisition: the acquisition of two languages entails strong competition in a highly interactive context and involves limited plasticity as a function of the timing of L2 learning. © 2010 Taylor & Francis.