Towards Precision Characterization of Communication Disorders using Models of Perceived Pragmatic Similarity

The diagnosis and treatment of individuals with communication disorders offers many opportunities for the application of speech technology, but research so far has not adequately considered: the diversity of conditions, the challenges of limited data, and the role of pragmatic deficits. This paper explores how a general-purpose model of perceived pragmatic similarity may overcome these limitations. It shows that a simple model can capture utterance aspects that are relevant to diagnosis of autism and of specific language impairment, outlines how it might support several use cases for clinicians and clients, and analyzes its performance and limitations.