My research utilizes an interdisciplinary approach to evaluate normal speech acquisition and transfer effects. I have taken a theoretical step-back from current models of speech motor control to re-evaluate the basic premise of “what is learned” during speech acquisition, and how this memory is represented. My dissertation project contrasts two broad learning theories from cognitive-psychology: rule-based versus instance-based learning. These theories can be contrasted based on memory encoding and retrieval characteristics, memory representation, and transfer pattern of learning. Current speech motor control theories are exclusively rule-based in their learning pattern and trajectory. However, general research in the area of motor learning provides evidence for instance-based learning. My dissertation contrasted these theories to investigate, for the first time, how speech memory representations are stored and transfer to similar stimuli.
Future work in the Speech Motor Control Lab will continue to extend this research by examining the various variables that may induce (or even bias) each learning theory. A current study is being conducted to replicate and extend my dissertation work. This study will examine the effects of syllable stress as a motor class variable in nonspeech words. If you are interested in participating in this study, please see Current Research Experiments for more information.
Future studies will also examine how instructions may bias encoding and retrieval of rule-based versus instance-based theories of motor learning. These instructions may interact with memory processing at different skill acquisition levels (e.g., early versus late in learning). Evaluation of instructions in how they may bias memory representations for each learning theory, and when instructions may impact skill acquisition are future goals of the lab.
Additionally, new technologies will be used to evaluate late-stage skill acquisition to further evaluate how speech memories change during learning. Evaluating speech motor control with accuracy variables alone may not be useful in well-learned, or automated, speech behaviors. Evaluation of kinematic data may allow for better observations in these later skill acquisition stages, and may be more translatable to the automated movements seen in typical speech production. The Speech Motor Control Lab is equipped with an NDI WAVE electromagnetic articulograph system to evaluate motor learning trajectories during late-stage skill acquisition.