Language Learning ISSN 0023-8333 Artificial Language Learning in Adults

This article briefly reviews some recent work on artificial language learning in children and adults. The final part of the article is devoted to a theoretical formulation of the language learning problem from a mechanistic neurobiological viewpoint and we show that it is logically possible to combine the notion of innate language constraints with, for example, the notion of domain general learning mechanisms. A growing body of empirical evidence suggests that the mechanisms involved in artificial language learning and in structured sequence processing are shared with those of natural language acquisition and natural language processing. Finally, by theoretically analyzing a formal learning model, we highlight Fodor’s insight that it is logically possible to combine innate, domain-specific constraints with domain-general learning mechanisms. Human languages are characterized by the “design features of language” (Hockett, 1963, 1987): discreteness, arbitrariness, productivity, and the du-ality of patterning (i.e., elements at one level are combined to construct el-ements at another). Somehow these properties arise from how the huma