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3. Reanalyzing neurocognitive data on the role of the motor system in speech perception within COSMO, a Bayesian perceptuo-motor model of speech communication

Author

Barnaud, Marie-Lou, Bessière, Pierre, Diard, Julien, Schwartz, Jean-Luc, GIPSA - Perception, Contrôle, Multimodalité et Dynamiques de la parole (GIPSA-PCMD), Département Parole et Cognition (GIPSA-DPC), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut des Systèmes Intelligents et de Robotique (ISIR), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), AMAC, Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Psychologie et NeuroCognition (LPNC ), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), and European Project: 339152,EC:FP7:ERC,ERC-2013-ADG,SPEECH UNIT(E)S(2014)

Subjects
Perceptuo-motor interactions, Motor perturbations, [SCCO]Cognitive science, Adverse conditions, [SCCO.NEUR]Cognitive science/Neuroscience, Speech perception, Repeated transcranial stimulation, Motor representations, [SCCO.COMP]Cognitive science/Computer science, Computational modeling, [SCCO.LING]Cognitive science/Linguistics, Neurocognitive architecture, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation
Abstract

International audience; While neurocognitive data provide clear evidence for the involvement of the motor system in speech perception, its precise role and the way motor information is involved in perceptual decision remain unclear. In this paper, we discuss some recent experimental results in light of COSMO, a Bayesian perceptuo-motor model of speech communication. COSMO enables us to model both speech perception and speech production with probability distributions relating phonological units with sensory and motor variables. Speech perception is conceived as a sensory-motor architecture combining an auditory and a motor decoder thanks to a Bayesian fusion process. We propose the sketch of a neuroanatomical architecture for COSMO, and we capitalize on properties of the auditory vs. motor decoders to address three neurocognitive studies of the literature. Altogether, this computational study reinforces functional arguments supporting the role of a motor decoding branch in the speech perception process .

Published
2017

4. Modeling the concurrent development of speech perception and production in a Bayesian framework

Author

Barnaud, Marie-Lou, Diard, Julien, Bessière, Pierre, Schwartz, Jean-Luc, Barnaud, Marie-Lou, and The multisensory-motor unity of speech - SPEECH UNIT(E)S - - EC:FP7:ERC2014-09-01 - 2019-08-31 - 339152 - VALID

Subjects
Statistical Learning, and Communication Skills in Biological Systems and Robots, Social, Cognitive, Motor, General Principles of Development and Learning, [SCCO.COMP] Cognitive science/Computer science, Development of Perceptual, Emotional, [SCCO] Cognitive science
Abstract

It is now widely accepted that there is a functional relationship between the speech perception and production systems in the human brain. However, the precise mechanisms and role of this relationship still remain debated. The question of invariance and robustness in categorization are set at the center of the debate: how is stable information extracted from the variable sensory input in order to achieve speech comprehension? In this context, auditory (resp. motor, perceptuo-motor) theories propose that speech is categorized thanks to auditory (resp. motor, perceptuo-motor) processes. However, experimental evidence is still scarce and does not allow to clearly distinguish between the current theories and determine whether invariance in speech perception is of an auditory or motor type. This is why we developed COSMO, a Bayesian model comparing sensory and motor processes in the form of probability distributions which enable both theoretical developments and quantitative simulations. A first significant result in COSMO is an indistinguishability theorem: it is only by simulations of adverse conditions or partial learning that the specificity of sensory vs. motor processing can emerge and provide a basis for evaluation of the specific role of each sub-system. We present the COSMO model, and how its sensory and motor sub-systems are learned, then we describe simulations exploring the way these sub-systems differ during speech categorization. We discuss the experimental results in the light of a “narrowband vs. wideband” interpretation: the sensory sub-system is more precisely tuned to the frequently learned sensory input and hence more efficient in recognizing these inputs, providing a “narrowband” system. Conversely, the motor sub-system is less accurate to recognize learned sensory inputs but it has better generalization properties, making it more robust to unexpected variability which would provide it with “wideband” characteristics.

Published
2015

6. Computer simulations of coupled idiosyncrasies in speech perception and speech production with COSMO, a perceptuo-motor Bayesian model of speech communication.

Author

Barnaud, Marie-Lou, Schwartz, Jean-Luc, Bessière, Pierre, and Diard, Julien

Subjects
*SPEECH perception, *ORAL communication, *HEARING disorders, *COGNITIVE psychology, *LEARNING
Abstract

The existence of a functional relationship between speech perception and production systems is now widely accepted, but the exact nature and role of this relationship remains quite unclear. The existence of idiosyncrasies in production and in perception sheds interesting light on the nature of the link. Indeed, a number of studies explore inter-individual variability in auditory and motor prototypes within a given language, and provide evidence for a link between both sets. In this paper, we attempt to simulate one study on coupled idiosyncrasies in the perception and production of French oral vowels, within COSMO, a Bayesian computational model of speech communication. First, we show that if the learning process in COSMO includes a communicative mechanism between a Learning Agent and a Master Agent, vowel production does display idiosyncrasies. Second, we implement within COSMO three models for speech perception that are, respectively, auditory, motor and perceptuo-motor. We show that no idiosyncrasy in perception can be obtained in the auditory model, since it is optimally tuned to the learning environment, which does not include the motor variability of the Learning Agent. On the contrary, motor and perceptuo-motor models provide perception idiosyncrasies correlated with idiosyncrasies in production. We draw conclusions about the role and importance of motor processes in speech perception, and propose a perceptuo-motor model in which auditory processing would enable optimal processing of learned sounds and motor processing would be helpful in unlearned adverse conditions. [ABSTRACT FROM AUTHOR]

Published
2019
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7. Proxemics models for human-aware navigation in robotics: Grounding interaction and personal space models in experimental data from psychology

Author

Barnaud, Marie-Lou, Morgado, Nicolas, Palluel-Germain, Richard, Diard, Julien, Spalanzani, Anne, Geometry and Probability for Motion and Action (E-MOTION), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire d'Informatique de Grenoble (LIG), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF), Laboratoire de Psychologie et NeuroCognition (LPNC), Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS), and Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SCCO.PSYC]Cognitive science/Psychology, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]
Abstract

International audience; In order to navigate in a social environment, a robot must be aware of social spaces, which include proximity and interaction-based constraints. Previous models of interaction and personal spaces have been inspired by studies in social psychology but not systematically grounded and validated with respect to experimental data. We propose to implement personal and interaction space models in order to replicate a classical psychology experiment. Our robotic simulations can thus be compared with experimental data from humans. Thanks to this comparison, we first show the validity of our models, examine the necessity of the interaction and personal spaces and discuss their geometric shape. Our experiments suggest that human-like robotic behavior can be obtained by using only correctly calibrated personal spaces (i.e., without explicit representation of interaction spaces and therefore, without the need to detect interactions between humans in the environment).

Published
2014

9. Assessing phonological learning in COSMO, a Bayesian model of speech communication

Author

Marie-Lou Barnaud, Jean-Luc Schwartz, Julien Diard, Pierre Bessière, GIPSA - Perception, Contrôle, Multimodalité et Dynamiques de la parole (GIPSA-PCMD), Département Parole et Cognition (GIPSA-DPC), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Laboratoire de Psychologie et NeuroCognition (LPNC ), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut des Systèmes Intelligents et de Robotique (ISIR), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), European Project: 339152,EC:FP7:ERC,ERC-2013-ADG,SPEECH UNIT(E)S(2014), Barnaud, Marie-Lou, and The multisensory-motor unity of speech - SPEECH UNIT(E)S - - EC:FP7:ERC2014-09-01 - 2019-08-31 - 339152 - VALID

Subjects
[SCCO]Cognitive science, [SCCO.COMP] Cognitive science/Computer science, [SCCO.COMP]Cognitive science/Computer science, [SCCO] Cognitive science, [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, [SCCO.LING] Cognitive science/Linguistics, [SCCO.LING]Cognitive science/Linguistics, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2017

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