Bridging Dynamical Systems and Optimal Trajectory Approaches to Speech Motor Control With Dynamic Movement Primitives

Abstract

Current models of speech motor control rely on either trajectory-based control (DIVA, GEPPETO, ACT) or a dynamical systems approach based on feedback control (Task Dynamics, FACTS). While both approaches have provided insights into the speech motor system, it is difficult to connect these findings across models given the distinct theoretical and computational bases of the two approaches. We propose a new extension of the most widely used dynamical systems approach, Task Dynamics, that incorporates many of the strengths of trajectory-based approaches, providing a way to bridge the theoretical divide between what have been two separate approaches to understanding speech motor control. The Task Dynamics (TD) model posits that speech gestures are governed by point attractor dynamics consistent with a critically damped harmonic oscillator. Kinematic trajectories associated with such gestures should therefore be consistent with a second-order dynamical system, possibly modified by blending with temporally overlapping gestures or altering oscillator parameters. This account of observed kinematics is powerful and theoretically appealing, but may be insufficient to account for deviations from predicted kinematics—i.e., changes produced in response to some external perturbations to the jaw, changes in control during acquisition and development, or effects of word/syllable frequency. Optimization, such as would be needed to minimize articulatory effort, is also incompatible with the current TD model, though the idea that the speech production systems economizes effort has a long history and, importantly, also plays a critical role in current theories of domain-general human motor control. To address these issues, we use Dynamic Movement Primitives (DMPs) to expand a dynamical systems framework for speech motor control to allow modification of kinematic trajectories by incorporating a simple, learnable forcing term into existing point attractor dynamics. We show that integration of DMPs with task-based point-attractor dynamics enhances the potential explanatory power of TD in a number of critical ways, including the ability to account for external forces in planning and optimizing both kinematic and dynamic movement costs. At the same time, this approach preserves the successes of Task Dynamics in handling multi-gesture planning and coordination.

Alice Turk and Stefanie Shattuck-Hufnagel (2020). Speech timing: implications for theories of phonology, phonetics, and speech motor control. (Oxford Studies in Phonology and Phonetics 5.) Oxford: Oxford University Press. Pp. xv + 370.

“…Nevertheless, the theoretical issues raised in Speech timing can focus much future research on computational and experimental aspects of relating phonological structure to the speech signal, including approaches that hybridise aspects of AP/TD and aspects of XT/3C (see e.g. Parrell & Lammert 2019).…”

Abstracts of the 8th International Conference on Speech Motor Control Groningen, August 2022

“…However, it has been predominantly applied to the kinematic analysis of healthy speakers. Although AP/TD approaches can handle a high amount of context-dependent articulatory variability, their flexibility has been recently described as being insufficient to account for perturbated or highly noisy speech movement contours commonly seen in impaired speakers (Parrell & Lammert, 2019). Even in fast syllable repetition tasks, which are considered kinematically less complex than running speech tasks, AP/TD cannot fully account for highly deviant speech motor behaviors of impaired speakers.…”

Articulatory coordination distinguishes complex segments from segment sequences

“…Even as the theory of the gesture has undergone development in its dynamic formulation, e.g. from an autonomous linear dynamical system with step activation (Saltzman & Munhall 1989) to a linear dynamical system with continuous activation (Kröger et al 1995) to a non-linear dynamical system (Sorensen & Gafos 2016) to hybrid interacting dynamical systems (Parrell & Lammert 2019), the assumption that speech movements are under the control of phonological goals has remained a constant working assumption.…”