An auditory-feedback-based model of speech production in the developing child

Abstract

The purpose of this project is to demonstrate that self-produced auditory feedback is sufficient to train a mapping between auditory target space and articulatory reference space under conditions in which the structures of speech production are undergoing considerable developmental restructuring. One challenge for competing theories that propose invariant constriction targets is that it is unclear what teaching signal could specify constriction location and degree so that a mapping between constriction target space and articulatory reference space can be learned. It is predicted that a model trained by auditory feedback will accomplish speech goals, in auditory target space, by continuously learning to use different articulatory configurations to adapt to the changing acoustical properties of the vocal tract during development. The Maeda articulatory synthesis part of the DIVA neural network model [Guenther et al., Psych. Rev. (in press)] was modified to reflect the development of the vocal tract by using measurements taken from MR images of children. The model accurately produced English vowels during development using various auditory target spaces. Stable constriction patterns were maintained throughout development using differing articulatory configurations to accomplish the same speech goals demonstrating that auditory feedback is sufficient to accommodate speech production development. [Work supported by NIHCD.]