Surprisal, memory constraints, and the noisy channel in human sentence processing

old_uid16293
titleSurprisal, memory constraints, and the noisy channel in human sentence processing
start_date2018/09/24
schedule14h-16h
onlineno
location_infosalle 1020
detailsthème « Probabilistic Models of Human Language »
summaryCours 2 - Human language comprehension poses some of the deepest scientific challenges in accounting for the capabilities of the human mind. In this lecture I describe several major advances we have recently made in this domain that have led to a state-of-the-art theory of language comprehension. First, I describe a detailed expectation-based theory of real-time language understanding, surprisal, that unifies three topics central to the field — ambiguity resolution, prediction, and syntactic complexity — and that finds broad empirical support. I alo cover work on memory constraints that seem to influence patterns of processing difficulty in sentence comprehension, independently of surprisal. Finally, I describe a “noisy-channel” theory which generalizes the expectation-based theory by removing the assumption of modularity between the processes of individual word recognition and sentence-level comprehension. This theory accounts for critical outstanding puzzles for previous approaches, and helps move us toward a theoretical integration of surprisal and memory.
responsiblesIsel