Automated Speech Analysis to Identify Clinical, Anatomical, and Pathological Variants of Primary Progressive Aphasia

Results of this cross-sectional study suggest that automated speech analysis of a short audio sample of connected speech yielded interpretable speech profiles that accurately distinguished PPA clinical, anatomical, and neuropathological subtypes. These automated speech profiles may serve as clinical tools to support differential diagnosis and longitudinal monitoring, particularly in settings where specialized speech-language assessment is limited.

Corresponding Author: Jet M. J. Vonk, PhD, PhD, Edward and Pearl Fein Memory and Aging Center, Department of Neurology, University of California San Francisco (UCSF), 675 Nelson Rising Ln, Ste 190, San Francisco, CA 94158 (jet.vonk@ucsf.edu).

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