Proceedings of the Annual Meeting of the Cognitive Science Society

This paper investigates the ability of a connectionist attractor network to learn a system analogous to part of the system of English verbal morphology. The model learned to produce phonological representations of stems and inflected forms in response to semantic inputs. The model was able to resolve several outstanding problems. It displayed all three stages of the characteristic U-shaped pattern of acquisition of the English past tense (early correct performance, a period of overgeneralizations and other errors, and eventual mastery). The network is also able to simulate direct access (the ability to create an inflected form directly from a semantic representation without having to first access an intermediate base form). The model was easily able to resolve homophonic verbs (such as ring and wring). In addition, the network was able to apply the past tense, third person -s and progressive -ing suffixes productively to novel forms and to display sensitivity to the subregularities that mark families of irregular past tense forms. The network also simulates the frequency by regularity interaction that has been found in reaction time studies of human subjects and provides a possible explanation for some hypothesized universal constraints upon morphological operations.