Target word prediction and paraphasia classification in spoken discourse
J. Donald Adams, Steven D. Bedrick, Gerasimos Fergadiotis, Kyle Gorman, Jan P. H. van Santen · 2017
We present a system for automatically detecting and classifying phonologically anomalous productions in the speech of individuals with aphasia.Working from transcribed discourse samples, our system identifies neologisms, and uses a combination of string alignment and language models to produce a lattice of plausible words that the speaker may have intended to produce.We then score this lattice according to various features, and attempt to determine whether the anomalous production represented a phonemic error or a genuine neologism.This approach has the potential to be expanded to consider other types of paraphasic errors, and could be applied to a wide variety of screening and therapeutic applications.