This CAREER award investigates how humans integrate a wide variety of information sources to achieve rapid, accurate natural language comprehension subject to the physical and cognitive constraints under which it takes place. The project's primary empirical focus is on reading, a mode of information exchange of unexceeded importance in literate societies. Reading involves a rapid sequence of targeted eye movements throughout a text -- recordable through modern eye-tracking technology -- from which noisy sensory input are obtained and integrated with prior knowledge to resolve perceptual and linguistic uncertainty. The central goal of this project is thus to develop, implement, and test a computational model of language comprehension and eye movement control in reading built on principles of probabilistic inference and rational action, using the tools of natural language processing (NLP) technology, reinforcement learning, and behavioral psycholinguistic experimentation.
The success of this project is likely to have major impact in the field of human sentence processing, bringing a new level of nuance and detail to both theory and data analysis, and will bear on broad current debates in cognitive science regarding rationality in cognition. Additionally, the results of this basic research project have a wide range of potential applications ranging from intelligent tutoring technology to language-impairment diagnosis to cognitive ergonomics. Together with this research program, the project involves an educational program including a new textbook on probabilistic models in the study of language, new undergraduate and graduate courses, and tutorials and courses on computational psycholinguistics at major conferences and summer institutes.
This CAREER award is co-funded by two directorates:: CISE/IIS and SBE/BCS.
