A team from MIT and the Massachusetts General Hospital believe that machine learning can play a part in better understanding speech disorders.
In a recent paper, they describe using a wearable device to collect accelerometer data to detect differences in people with Muscle Tension Dysphonia (MTD) and a control group. After such individuals with MTD had received therapy for the condition, their behaviors appeared to converge with that of the control group.
“We believe this approach could help detect disorders that are exacerbated by vocal misuse, and help to empirically measure the impact of voice therapy,” the authors say. “Our long-term goal is for such a system to be used to alert patients when they are using their voices in ways that could lead to problems.”
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