Automatically Calculated Context-Sensitive Features of Connected Speech Improve Prediction of Impairment in Alzheimer's Disease
These results provide novel evidence that metrics related to contextualized word choices, particularly the surprisal of an individual's words, capture variance in degree of cognitive decline in AD.
Authors
- Rachel Ostrand (ORCID: https://orcid.org/0000-0001-5491-7656)
- Graham Flick (ORCID: https://orcid.org/0000-0001-9183-4040)
Institutions
- IBM (United States) (US)
- Baycrest Hospital (CA)
- New York University (US)
Publication Details
- Journal
- Journal of Speech Language and Hearing Research
- Published
- 2025-10-14
- DOI
- https://doi.org/10.1044/2025_jslhr-24-00297
- Citations
- 1
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 1.47
Funders
- University of Pittsburgh
- National Institutes of Health
- Natural Sciences and Engineering Research Council of Canada