The Acquisition of Lexical and Grammatical Aspect in a Self-Organizing Feature-Map Model

This study uses self-organizing feature maps to model the acquisition of lexical and grammatical aspect. Previous research has identified a strong association between lexical aspect and grammatical aspect in child language, on the basis of which some researchers proposed innate semantic categories (Bickerton, 1984) or prelinguistic semantic space (Slobin, 1985). Our simulations indicate that this association can be modeled by self-organization and Hebbian learning principles in a feature-map model, without making particular assumptions about the structure of innate knowledge. In line with results from Li (1999), our study further attests to the utility of self-organizing neural networks in the study of language acquisition.