Bilingual Lexical Representation in a Self-Organizing Neural Network Model

In this paper we present a self-organizing neural network model of bilingual lexical development. We focus on how the representational structure of the bilingual lexicon can emerge, develop, and change as a function of the learning history. Our results show that (1) distinct representations for the two lexicons can develop in our network during simultaneous acquisition, (2) the representational structure is highly dependent on the onset time of L2 learning if the two languages are learned sequentially, and (3) L2 representation becomes parasitic on L1 representation when L2 learning 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 limited plasticity as a function of the timing of learning.