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Integrate, yes, but what and how? A computational approach of sensorimotor fusion in speech

Published online by Cambridge University Press:  24 June 2013

Raphaël Laurent
Affiliation:
GIPSA-Lab – CNRS UMR 5216, Grenoble University, 38402 Saint Martin D'Hères Cedex, France. Raphael.Laurent@gipsa-lab.grenoble-inp.frhttp://www.gipsa-lab.grenoble-inp.fr/page_pro.php?vid=1238Jean-Luc.Schwartz@gipsa-lab.grenoble-inp.frhttp://www.gipsa-lab.grenoble-inp.fr/~jean-luc.schwartz/http://www.gipsa-lab.grenoble-inp.fr/~clement.moulin-frier/cv_en.html e-Motion team - INRIA Rhône-Alpes, 38334 Saint Ismier Cedex, France.
Clément Moulin-Frier
Affiliation:
GIPSA-Lab – CNRS UMR 5216, Grenoble University, 38402 Saint Martin D'Hères Cedex, France. Raphael.Laurent@gipsa-lab.grenoble-inp.frhttp://www.gipsa-lab.grenoble-inp.fr/page_pro.php?vid=1238Jean-Luc.Schwartz@gipsa-lab.grenoble-inp.frhttp://www.gipsa-lab.grenoble-inp.fr/~jean-luc.schwartz/http://www.gipsa-lab.grenoble-inp.fr/~clement.moulin-frier/cv_en.html FLOWERS team - INRIA Bordeaux Sud-Ouest, 33405 Talence Cedex, France. clement.moulin-frier@inria.fr
Pierre Bessière
Affiliation:
e-Motion team - INRIA Rhône-Alpes, 38334 Saint Ismier Cedex, France. Laboratoire de Physiologie de la Perception et de l'Action – CNRS UMR 7152, Collège de France,75005 Paris, France. Pierre.Bessiere@College-de-France.frhttp://www.Bayesian-Programming.org
Jean-Luc Schwartz
Affiliation:
GIPSA-Lab – CNRS UMR 5216, Grenoble University, 38402 Saint Martin D'Hères Cedex, France. Raphael.Laurent@gipsa-lab.grenoble-inp.frhttp://www.gipsa-lab.grenoble-inp.fr/page_pro.php?vid=1238Jean-Luc.Schwartz@gipsa-lab.grenoble-inp.frhttp://www.gipsa-lab.grenoble-inp.fr/~jean-luc.schwartz/http://www.gipsa-lab.grenoble-inp.fr/~clement.moulin-frier/cv_en.html
Julien Diard
Affiliation:
Laboratoire de Psychologie et NeuroCognition – CNRS UMR 5105, Grenoble University, 38040 Grenoble Cedex 9, France. Julien.Diard@upmf-grenoble.frhttp://diard.wordpress.com/

Abstract

We consider a computational model comparing the possible roles of “association” and “simulation” in phonetic decoding, demonstrating that these two routes can contain similar information in some “perfect” communication situations and highlighting situations where their decoding performance differs. We conclude that optimal decoding should involve some sort of fusion of association and simulation in the human brain.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2013 

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