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Prediction, explanation, and the role of generative models in language processing

Published online by Cambridge University Press:  10 May 2013

Thomas A. Farmer
Affiliation:
Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY 14627-0268. tfarmer@bcs.rochester.edumbrown@bcs.rochester.edumtan@bcs.rochester.edu Center for Language Sciences, University of Rochester, Rochester, NY 14627-0268
Meredith Brown
Affiliation:
Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY 14627-0268. tfarmer@bcs.rochester.edumbrown@bcs.rochester.edumtan@bcs.rochester.edu
Michael K. Tanenhaus
Affiliation:
Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY 14627-0268. tfarmer@bcs.rochester.edumbrown@bcs.rochester.edumtan@bcs.rochester.edu

Abstract

We propose, following Clark, that generative models also play a central role in the perception and interpretation of linguistic signals. The data explanation approach provides a rationale for the role of prediction in language processing and unifies a number of phenomena, including multiple-cue integration, adaptation effects, and cortical responses to violations of linguistic expectations.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2013 

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