 
Summary: To appear in `Probabilistic Linguistics', edited by Rens Bod,
Jennifer Hay, and Stefanie Jannedy, MIT Press, 2002
Probabilistic Modeling in Psycholinguistics: Linguistic
Comprehension and Production
Dan Jurafsky
Probability is not really about numbers; it is about the structure of reasoning
Glenn Shafer, cited in Pearl (1988)
1 Introduction
It must certainly be accounted a paradox that probabilistic modeling is simultaneously one of the
oldest and one of the newest areas in psycholinguistics. Much research in linguistics and psycholin
guistics in the 1950s was statistical and probabilistic. But this research disappeared throughout the
60's, 70's, and 80's. In a highly unscientific survey (conducted by myself) of six college text
books and handbooks in psycholinguistics published in the last 10 years, not a single one of them
mentions the word `probability' in the index.
This omission is astonishing when we consider that the input to language comprehension is
noisy, ambiguous, and unsegmented. In order to deal with these problems, computational models
of speech processing, by contrast, have had to rely on probabilistic models for over 30 years.
Computational techniques for processing of text, an input medium which is much less noisy than
speech, rely just as heavily on probability theory. Just to pick an arbitrary indicator, 77% of the
papers in the year 2000 annual conference of the Association for Computational Linguistics relied
