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

The purpose of this project was 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. (1998)] was modified to reflect the development of the vocal tract by using measurements taken from MR images of children. After training, the model was able to maintain the 11 English vowel targets in auditory planning space, utilizing varying articulatory configurations, despite morphological changes that occur during development. The vocal tract constriction pattern (derived from the vocal tract area function) as well as the formant values varied during the course of development in correspondence with morphological changes in the structures involved with speech production. The model was also able to account for motor equivalent speech production under conditions in which one or more of the articulators was restricted, such as in the case of a bite block.