Paper: A Model of Discourse Predictions in Human Sentence Processing

ACL ID D11-1028
Title A Model of Discourse Predictions in Human Sentence Processing
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2011
Authors

This paper introduces a psycholinguistic model of sentence processing which combines a Hidden Markov Model noun phrase chun- ker with a co-reference classifier. Both mod- els are fully incremental and generative, giv- ing probabilities of lexical elements condi- tional upon linguistic structure. This allows us to compute the information theoretic mea- sure of surprisal, which is known to correlate with human processing effort. We evaluate our surprisal predictions on the Dundee corpus of eye-movement data show that our model achieve a better fit with human reading times than a syntax-only model which does not have access to co-reference information.