Date created: | Last Updated:

Category: Project

Description: In this project we develop and test a corpus-based, rational (Bayesian) model of incremental argument interpretation. The model predicts processing difficulty during sentence comprehension as a function of the Bayesian surprise associated with changes in expectations over possible argument interpretations. The model is tested against reading times from a moving window self-paced reading experiment on Swedish. The ability of the model to predict reading times is also compared to that of a 'linguistic' model, which predicts reading times directly on th basis of morphosyntactic features, animacy and verb semantics.