Hostname: page-component-78c5997874-g7gxr Total loading time: 0 Render date: 2024-11-19T17:44:04.621Z Has data issue: false hasContentIssue false

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 

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

Bessière, P., Laugier, C. & Siegwart, R. ed. (2008) Probabilistic reasoning and decision making in sensory-motor systems, volume 46 of Springer tracts in advanced robotics. Springer-Verlag.Google Scholar
Castellini, C., Badino, L., Metta, G., Sandini, G., Tavella, M., Grimaldi, M. & Fadiga, L. (2011) The use of phonetic motor invariants can improve automatic phoneme discrimination. PLoS ONE 6(9):e24055.Google Scholar
Colas, F., Diard, J. & Bessière, P. (2010) Common Bayesian models for common cognitive issues. Acta Biotheoretica 58(2–3):191216.Google Scholar
D'Ausilio, A., Bufalari, I., Salmas, P. & Fadiga, L. (2012b) The role of the motor system in discriminating degraded speech sounds. Cortex 48:882–87.Google Scholar
Lebeltel, O., Bessière, P., Diard, J. & Mazer, E. (2004) Bayesian robot programming. Autonomous Robots 16(1):4979.Google Scholar
Meister, I. G., Wilson, S. M., Deblieck, C., Wu, A. D. & Iacoboni, M. (2007) The essential role of premotor cortex in speech perception. Current Biology 17:1692–96.Google Scholar
Moulin-Frier, C., Laurent, R., Bessière, P., Schwartz, J.-L. & Diard, J. (2012) Adverse conditions improve distinguishability of auditory, motor and perceptuo-motor theories of speech perception: An exploratory Bayesian modeling study. Language and Cognitive Processes 27(7–8):1240–63.Google Scholar
Schwartz, J.-L., Basirat, A., Ménard, L. & Sato, M. (2012) The perception-for-action-control theory (PACT): A perceptuo-motor theory of speech perception. Journal of Neurolinguistics 25(5):336–54.Google Scholar
Zekveld, A. A., Heslenfeld, D. J., Festen, J. M. & Schoonhoven, R. (2006) Top-down and bottom-up processes in speech comprehension. NeuroImage 32:1826–36.Google Scholar