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

Ward, Nigel G., Segura, Andres, Bugarini, Georgina, Lehnert-LeHouillier, Heike, Liu, Dancheng, Xiong, Jinjun, Fuentes, Olac

arXiv.org Artificial Intelligence 

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 role of pragmatic deficits, and the challenges of limited data. This paper explores how a general-purpose model of perceived pragmatic similarity may overcome these limitations. It explains how it might support several use cases for clinicians and clients, and presents evidence that a simple model can provide value, and in particular can capture utterance aspects that are relevant to diagnoses of autism and specific language impairment.

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