COSMO: a Bayesian model of sensorimotor interactions in speech perception
Ph.D thesis of Raphael Laurent (2014)
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 three main results.
- (i) In a set of precisely defined “perfect conditions”, auditory and motor theories of speech perception are indistinguishable.
- (ii) 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 vs. motor-wideband” property.
- (iii) 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.