The FACTS model of speech motor control: Fusing state estimation and task-based control

Abstract

We present a new computational model of speech motor control: the Feedback-Aware Control of Tasks in Speech or FACTS model. FACTS employs a hierarchical state feedback control architecture to control simulated vocal tract and produce intelligible speech. The model includes higher-level control of speech tasks and lower-level control of speech articulators. The task controller is modeled as a dynamical system governing the creation of desired constrictions in the vocal tract, after Task Dynamics. Both the task and articulatory controllers rely on an internal estimate of the current state of the vocal tract to generate motor commands. This estimate is derived, based on efference copy of applied controls, from a forward model that predicts both the next vocal tract state as well as expected auditory and somatosensory feedback. A comparison between predicted feedback and actual feedback is then used to update the internal state prediction. FACTS is able to qualitatively replicate many characteristics of the human speech system: the model is robust to noise in both the sensory and motor pathways, is relatively unaffected by a loss of auditory feedback but is more significantly impacted by the loss of somatosensory feedback, and responds appropriately to externally-imposed alterations of auditory and somatosensory feedback. The model also replicates previously hypothesized trade-offs between reliance on auditory and somatosensory feedback and shows for the first time how this relationship may be mediated by acuity in each sensory domain. These results have important implications for our understanding of the speech motor control system in humans. Speaking is one of the most complex motor tasks humans perform, but it’s neural and computational bases are not well understood. We present a new computational model that generates speech movements by comparing high-level language production goals with an internal estimate of the current state of the vocal tract. This model reproduces many key human behaviors, including making appropriate responses to multiple types of external perturbations to sensory feedback, and makes a number of novel predictions about the speech motor system. These results have implications for our understanding of healthy speech as well as speech impairments caused by neurological disorders. They also suggest that the mechanisms of control are shared between speech and other motor domains.