Motor control primitives arising from a dynamical systems model of vocal tract articulation

Abstract

We have previously presented a computational approach to derive interpretable movement primitives from speech articulation data using a convolutive Nonnegative Matrix Factorization with sparseness constraints (cNMFsc) technique (Ramanarayanan et al., Interspeech 2011; Ramanarayanan et al., J. Acoust. Soc. Am. 134(2), in press). However, it is not clear whether finding such a dictionary of primitives can be useful for speech motor control, particularly in finding a low-dimensional subspace for such control. In this paper, we examine this possibility in two steps. First, we use the iterative Linear Quadratic Gaussian (iLQG) algorithm to derive a set of control inputs to a dynamical systems model of the vocal tract that produces a desired movement sequence. Second, we use the cNMFsc algorithm to find a small dictionary of control input “primitives'' that can be used to drive said dynamical systems model of the vocal tract to produce the desired range of articulatory movement. We show, using both qualitative ...