Paper: A Probabilistic Earley Parser As A Psycholinguistic Model

ACL ID N01-1021
Title A Probabilistic Earley Parser As A Psycholinguistic Model
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2001
Authors
  • John Hale (Johns Hopkins University, Baltimore MD)

In human sentence processing, cognitive load can be de ned many ways. This report considers a de ni- tion of cognitive load in terms of the total probability of structural options that have been discon rmed at some point in a sentence: the surprisal of word w i given its pre x w 0:::i−1 on a phrase-structural lan- guage model. These loads can be e ciently calcu- lated using a probabilistic Earley parser (Stolcke, 1995) which is interpreted as generating predictions about reading time on a word-by-word basis. Un- der grammatical assumptions supported by corpus- frequency data, the operation of Stolcke’s probabilis- tic Earley parser correctly predicts processing phe- nomena associated with garden path structural am- biguity and with the subject/object relative asym- metry.