ArticlePloS one2019
Computer simulations of coupled idiosyncrasies in speech perception and speech production with COSMO, a perceptuo-motor Bayesian model of speech communication.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Brain-inspired model for early vocal learning and correspondence matching using free-energy optimization.PLoS computational biology · 2021Article
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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.
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