Marie-Lou Barnaud

The complementary roles of auditory and motor information evaluated in a Bayesian perceptuo-motor model of speech perception

There is a consensus concerning the view that both auditory and motor representations intervene in the perceptual processing of speech units. However, the question of the functional role of each of these systems remains seldom addressed and poorly understood. We capitalized on the formal framework of Bayesian Programming to develop COSMO (Communicating Objects using Sensory-Motor Operations), an integrative model that allows principled comparisons of purely motor or purely auditory implementations of a speech perception task and tests the gain of efficiency provided by their Bayesian fusion. Here, we show 3 main results: (a) In a set of precisely defined “perfect conditions,” auditory and motor theories of speech perception are indistinguishable; (b) When a learning process that mimics speech development is introduced into COSMO, it departs from these perfect conditions. Then auditory recognition becomes more efficient than motor recognition in dealing with learned stimuli, while motor recognition is more efficient in adverse conditions. We interpret this result as a general “auditory-narrowband versus motor-wideband” property; and (c) Simulations of plosive-vowel syllable recognition reveal possible cues from motor recognition for the invariant specification of the place of plosive articulation in context that are lacking in the auditory pathway. This provides COSMO with a second property, where auditory cues would be more efficient for vowel decoding and motor cues for plosive articulation decoding. These simulations provide several predictions, which are in good agreement with experimental data and suggest that there is natural complementarity between auditory and motor processing within a perceptuo-motor theory of speech perception.

Phonology in the mirror: Comment on "Towards a Computational Comparative Neuroprimatology: Framing the language-ready brain" by Michael A. Arbib.

The contribution by M.A. Arbib over the years and as it appears summarized and conceptualized in this paper is admirable, extremely impressive, and very convincing in many aspects. A key value of this work is that it systematically attempts to introduce formal conceptualization and modeling in the reasoning about facts and interpretations.

Sensorimotor learning in a Bayesian computational model of speech communication

Although sensorimotor exploration is a basic process within child development, clear views on the underlying computational processes remain challenging. We propose to compare eight algorithms for sensorimotor exploration, based on three components: “accommodation” performing a compromise between goal babbling and social guidance by a master, “local extrapolation” simulating local exploration of the sensorimotor space to achieve motor generalizations and “idiosyncratic babbling” which favors already explored motor commands when they are efficient. We will show that a mix of these three components offers a good compromise enabling efficient learning while reducing exploration as much as possible.

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

&NA; 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.

COSMO, a Bayesian computational model of speech communication: Assessing the role of sensory vs. motor knowledge in speech perception

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.