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.
@article{arxiv.2409.09170,
title = {Towards Precision Characterization of Communication Disorders using Models of Perceived Pragmatic Similarity},
author = {Nigel G. Ward and Andres Segura and Georgina Bugarini and Heike Lehnert-LeHouillier and Dancheng Liu and Jinjun Xiong and Olac Fuentes},
journal= {arXiv preprint arXiv:2409.09170},
year = {2024}
}