Adverse conditions improve distinguishability of auditory, motor, and perceptuo-motor theories of speech perception: An exploratory Bayesian modelling study

Abstract

In this paper, we put forward a computational framework for the comparison between motor, auditory, and perceptuo-motor theories of speech communication. We first recall the basic arguments of these three sets of theories, either applied to speech perception or to speech production. Then we expose a unifying Bayesian model able to express each theory in a probabilistic way. Focusing on speech perception, we demonstrate that under two hypotheses, regarding communication noise and inter-speaker variability, providing perfect conditions for speech communication, motor, and auditory theories are indistinguishable. We then degrade successively each hypothesis to study the distinguishability of the different theories in “adverse” conditions. We first present simulations on a simplified implementation of the model with mono-dimensional sensory and motor variables, and secondly we consider a simulation of the human vocal tract providing more realistic auditory and articulatory variables. Simulation results allow us to emphasise the respective roles of motor and auditory knowledge in various conditions of speech perception in adverse conditions, and to suggest some guidelines for future studies aiming at assessing the role of motor knowledge in speech perception.

Keywords:

• Auditory, motor, and perceptuo-motor theories of speech communication
• Bayesian modelling
• Speech perception in adverse conditions
• Model distinguishability

Notes

¹Notice that the perceptuo-motor model is actually different from both the auditory and the motor models here. Indeed, since it is based on a fusion of the perceptual and motor inputs, it questions twice the classifier P(O ^L ‌ S) (equal to P(O ^S ‌ S) in this situation) and keeps only coherent answers, thus decreasing the error rate.