Speech and Rhetorical Studies Commons^™

Automating Intended Target Identification For Paraphasias In Discourse Using A Large Language Model, Alexandra C. Salem, Robert Gale, Mikala S. Fleegle, Gerasimos Fergadiotis, Steven Bedrick

Speech and Hearing Sciences Faculty Publications and Presentations

Purpose:

To date, there are no automated tools for the identification and fine-grained classification of paraphasias within discourse, the production of which is the hallmark characteristic of most people with aphasia (PWA). In this work, we fine-tune a large language model (LLM) to automatically predict paraphasia targets in Cinderella story retellings.

Method:

Data consisted of 332 Cinderella story retellings containing 2,489 paraphasias from PWA, for which research assistants identified their intended targets. We supplemented these training data with 256 sessions from control participants, to which we added 2,415 synthetic paraphasias. We conducted four experiments using different training data configurations to …