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

We present a method to derive a small number of speech motor control “primitives” that can produce linguistically-interpretable articulatory movements. We envision that such a dictionary of primitives can be useful for speech motor control, particularly in finding a lowdimensional subspace for such control. First, we use the iterative Linear Quadratic Gaussian (iLQG) algorithm to derive (for a set of utterances) a set of stochastically optimal control inputs to a dynamical systems model of the vocal tract that produces desired movement sequences. Second, we use a convolutive Nonnegative Matrix Factorization with sparseness constraints (cNMFsc) algorithm to find a small dictionary of control input primitives that can be used to reproduce the aforementioned optimal control inputs that produce the observed articulatory movements. Such a primitives-based framework could help inform theories of speech motor control and coordination.