Proceedings of the Annual Meeting of the Cognitive Science Society

Research in theoretical linguistics has shown that human languages require abstract and highly detailed grammaticalrepresentations. However, we understand surprisingly little about the mechanisms through which these representations areacquired. What kinds of statistical relationships would learners need to compute to construct representations like those positedby linguistic theory? We created miniature languages containing patterns found in natural languages and also patterns notfound in natural languages. We showed that complex word-order contingencies are acquired only when they correlate withmorphological patterns like those in natural languages. We then asked how learning changes when the statistical evidence forthese patterns is manipulated. These experiments illuminate the nature of learners’ computations and the units over which theyare performed.