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Forward modelling requires intention recognition and non-impoverished predictions

Published online by Cambridge University Press:  24 June 2013

Jan P. de Ruiter  and
Chris Cummins
Jan P. de Ruiter
Affiliation:
Department of Psycholinguistics, Bielefeld University, 33501 Bielefeld, Germany. jan.deruiter@uni-bielefeld.dehttp://www.uni-bielefeld.de/lili/personen/jruiter/chris.cummins@uni-bielefeld.de
Chris Cummins
Affiliation:
Department of Psycholinguistics, Bielefeld University, 33501 Bielefeld, Germany. jan.deruiter@uni-bielefeld.dehttp://www.uni-bielefeld.de/lili/personen/jruiter/chris.cummins@uni-bielefeld.de
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Abstract

We encourage Pickering & Garrod (P&G) to implement this promising theory in a computational model. The proposed theory crucially relies on having an efficient and reliable mechanism for early intention recognition. Furthermore, the generation of impoverished predictions is incompatible with a number of key phenomena that motivated P&G's theory. Explaining these phenomena requires fully specified perceptual predictions in both comprehension and production.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 36 , Issue 4 , August 2013 , pp. 351
Copyright
Copyright © Cambridge University Press 2013 

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References

De Ruiter, J. P. & Cummins, C. (2012) A model of intentional communication: AIRBUS (Asymmetric Intention Recognition with Bayesian Updating of Signals) . In: Proceedings of SemDial 2012, ed. Brown-Schmidt, S., Ginzburg, J. & Larsson, S., pp. 149–50.Google Scholar
De Ruiter, J. P., Mitterer, H. & Enfield, N. J. (2006) Predicting the end of a speaker's turn; a cognitive cornerstone of conversation. Language 82(3):515–35.Google Scholar
Dell, G. S. (1986) A spreading-activation theory of retrieval in sentence production. Psychological Review 93:283–321.Google Scholar
DeVault, D., Sagae, K. & Traum, D. (2011) Incremental interpretation and prediction of utterance meaning for interactive dialogue. Dialogue and Discourse 2(1):143–70.Google Scholar
Heinks-Maldonado, T. H., Nagarajan, S. S. & Houde, J. F. (2006) Magnetoencephalographic evidence for a precise forward model in speech production. NeuroReport 17(13):1375–79.Google Scholar
Levelt, W. J. M. (1989) Speaking: From intention to articulation. MIT Press.Google Scholar
Levinson, S. C. (1983) Pragmatics. Cambridge University Press.Google Scholar
Levinson, S. C. (1995) Interaction biases in human thinking. In: Social intelligence and interaction, ed. Goody, E. N., pp. 221–60. Cambridge University Press.Google Scholar
Magyari, L. & De Ruiter, J. P. (2012) Prediction of turn-ends based on anticipation of upcoming words. Frontiers in Psychology 3:376.Google Scholar
Marslen-Wilson, W. D. (1973) Linguistic structure and speech shadowing at very short latencies. Nature 244:522–23.Google Scholar
Pickering, M. J. & Garrod, S. (2007) Do people use language production to make predictions during comprehension? Trends in Cognitive Sciences 11(3): 105–10.Google Scholar
Stivers, T., Enfield, N. J., Brown, P., Englert, C., Hayashi, M., Heinemann, T., Hoymann, G., Rossano, F., De Ruiter, J. P., Yoon, K. E., & Levinson, S. C. (2009) Universals and cultural variation in turn-taking in conversation. Proceedings of the National Academy of Sciences of the United States of America 106(26):10587–92.Google Scholar
Tourville, J. A., Reily, K. J. & Guenther, F. K. (2008) Neural mechanisms underlying auditory feedback control of speech. NeuroImage 39:1429–43.Google Scholar