Paraphasia Detection

Paraphasia detection, the automated identification of speech errors characteristic of aphasia, aims to improve the efficiency and consistency of clinical assessment by reducing reliance on manual transcription and analysis. Current research focuses on moving beyond simple binary classification (presence/absence) to multi-class detection of different paraphasia types, employing end-to-end sequence-to-sequence models and generative pretrained transformers to directly process speech or transcripts. These advancements offer the potential for faster, more objective aphasia diagnosis and personalized treatment planning.