Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-21T17:19:05.694Z Has data issue: false hasContentIssue false
  • English
  • Français

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
Get access Rights & Permissions [Opens in a new window]

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 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

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