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The sensorimotor and social sides of the architecture of speech

Published online by Cambridge University Press:  17 December 2014

Giovanni Pezzulo
Affiliation:
Institute of Cognitive Sciences and Technologies, National Research Council, 00185 Rome, Italy. giovanni.pezzulo@istc.cnr.itlaura.barca@istc.cnr.ithttps://sites.google.com/site/giovannipezzulo/https://sites.google.com/site/laurabarcahomepage/
Laura Barca
Affiliation:
Institute of Cognitive Sciences and Technologies, National Research Council, 00185 Rome, Italy. giovanni.pezzulo@istc.cnr.itlaura.barca@istc.cnr.ithttps://sites.google.com/site/giovannipezzulo/https://sites.google.com/site/laurabarcahomepage/
Alessando D'Ausilio
Affiliation:
Robotics, Brain and Cognitive Sciences Department, Italian Institute of Technology, 16163 Genova, Italy. alessandro.dausilio@iit.ithttp://www.iit.it/people/robotics-brain-and-cognitive-sciences-mirror-neurons-and-interaction-lab/researcher/alessandro-dausilio.html

Abstract

Speech is a complex skill to master. In addition to sophisticated phono-articulatory abilities, speech acquisition requires neuronal systems configured for vocal learning, with adaptable sensorimotor maps that couple heard speech sounds with motor programs for speech production; imitation and self-imitation mechanisms that can train the sensorimotor maps to reproduce heard speech sounds; and a “pedagogical” learning environment that supports tutor learning.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2014 

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References

Ackermann, H. (2008) Cerebellar contributions to speech production and speech perception: Psycholinguistic and neurobiological perspectives. Trends in Neurosciences 31(6):265–72. doi: 10.1016/j.tins.2008.02.011.Google Scholar
Brainard, M. S. & Doupe, A. J. (2002) What songbirds teach us about learning. Nature 417:351–58.Google Scholar
Caligiore, D., Pezzulo, G., Miall, R. C. & Baldassarre, G. (2013) The contribution of brain sub-cortical loops in the expression and acquisition of action understanding abilities. Neuroscience and Biobehavioral Reviews 37(10):2504–15.Google Scholar
Canevari, C., Badino, L., D'Ausilio, A., Fadiga, L. & Metta, G. (2013) Modeling speech imitation and ecological learning of auditory-motor maps. Frontiers in Psychology 4:364.Google Scholar
Chersi, F., Ferro, M., Pezzulo, G. & Pirrelli, V. (2014) Topological self-organization and prediction learning can support both action and lexical chains in the brain. Topics in Cognitive Science 6(3):476–91.Google Scholar
Csibra, G. & Gergely, G. (2011) Natural pedagogy as evolutionary adaptation. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences 366:1149–57.Google Scholar
D'Ausilio, A., Craighero, L. & Fadiga, L. (2012) The contribution of the frontal lobe to the perception of speech. Journal of Neurolinguistics 25:328–35.Google Scholar
Dehaene, S. & Cohen, L. (2007) Cultural recycling of cortical maps. Neuron 56(2):384–98. doi: 10.1016/j.neuron.2007.10.004.Google Scholar
Dindo, H., Zambuto, D. & Pezzulo, G. (2011) Motor simulation via coupled internal models using sequential Monte Carlo. In: Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence (IJCAI), Barcelona, Catalonia, Spain, 16–22 July 2011, ed. Walsh, Toby, pp. 2113–19. AAAI Press/International Joint Conferences on Artificial Intelligence.Google Scholar
Fadiga, L., Craighero, L. & D'Ausilio, A. (2009) Broca's area in language, action, and music. Annals of the New York Academy of Sciences 1169(1):448–58. doi: 10.1111/j.1749-6632.2009.04582.x.Google Scholar
Friston, K. (2010) The free-energy principle: A unified brain theory? Nature Reviews Neuroscience 11:127–38.Google Scholar
Guenther, F. H. & Perkell, J. S. (2004) A neural model of speech production and its application to studies of the role of auditory feedback in speech. In: Speech motor control in normal and disordered speech, ed. Maassen, B., Kent, R., Peters, H., Lieshout, P. Van & Hulstijn, W., pp. 2949. Oxford University Press.Google Scholar
Hinton, G. E. (2007) Learning multiple layers of representation. Trends in Cognitive Sciences 11:428–34.Google Scholar
Kiebel, S. J., Daunizeau, J. & Friston, K. J. (2008) A hierarchy of time-scales and the brain. PLOS Computational Biology 4:e1000209.Google Scholar
Merker, B. (2012) The vocal learning constellation: Imitation, ritual culture, encephalization. In: Music, language and human evolution, ed. Bannan, N., pp. 215–60. Oxford University Press.Google Scholar
Moore, R. K. (2007) PRESENCE: A human-inspired architecture for speech-based human-machine interaction. IEEE Transactions on Computers 56:1176–88.Google Scholar
Pezzulo, G. (2012a) An Active Inference view of cognitive control. Frontiers in Psychology 3:478. doi: 10.3389/fpsyg.2012.00478.Google Scholar
Pezzulo, G. (2012b) The “Interaction Engine”: A common pragmatic competence across linguistic and non-linguistic interactions. IEEE Transactions on Autonomous Mental Development 4:105–23.Google Scholar
Pezzulo, G. (2013) Studying mirror mechanisms within generative and predictive architectures for joint action. Cortex 49:2968–69.Google Scholar
Pezzulo, G., Donnarumma, F. & Dindo, H. (2013) Human sensorimotor communication: A theory of signaling in online social interactions. PLOS ONE 8:e79876.CrossRefGoogle ScholarPubMed
Pickering, M. J. & Garrod, S. (2013) An integrated theory of language production and comprehension. Behavioral and Brain Sciences 36(4):329–47.Google Scholar
Prather, J. F., Peters, S., Nowicki, S. & Mooney, R. (2008) Precise auditory–vocal mirroring in neurons for learned vocal communication. Nature 451:305–10.Google Scholar
Sebanz, N., Bekkering, H. & Knoblich, G. (2006) Joint action: Bodies and minds moving together. Trends in Cognitive Sciences 10:7076.Google Scholar
Yildiz, I. B., von Kriegstein, K. & Kiebel, S. J. (2013) From birdsong to human speech recognition: Bayesian inference on a hierarchy of nonlinear dynamical systems. PLOS Computational Biology 9:e1003219.Google Scholar