Using Automatic Assessment of Speech Production to Predict Current and Future Cognitive Function in Older Adults

Overview

Journal J Geriatr Psychiatry Neurol

Publisher Sage Publications

Specialties Geriatrics
Neurology
Psychiatry

Date 2020 Jul 30

PMID 32723128

Citations 13

Authors

Rachel Ostrand

John Gunstad

Affiliations

Soon will be listed here.

Abstract

Neurodegenerative conditions like Alzheimer disease affect millions and have no known cure, making early detection important. In addition to memory impairments, dementia causes substantial changes in speech production, particularly lexical-semantic characteristics. Existing clinical tools for detecting change often require considerable expertise or time, and efficient methods for identifying persons at risk are needed. This study examined whether early stages of cognitive decline can be identified using an automated calculation of lexical-semantic features of participants' spontaneous speech. Unimpaired or mildly impaired older adults (N = 39, mean 81 years old) produced several monologues (picture descriptions and expository descriptions) and completed a neuropsychological battery, including the Modified Mini-Mental State Exam. Most participants (N = 30) returned one year later for follow-up. Lexical-semantic features of participants' speech (particularly lexical frequency) were significantly correlated with cognitive status at the same visit and also with cognitive status one year in the future. Thus, automated analysis of speech production is closely associated with current and future cognitive test performance and could provide a novel, scalable method for longitudinal tracking of cognitive health.

Citing Articles

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Natural language processing-based classification of early Alzheimer's disease from connected speech.

Balabin H, Tamm B, Spruyt L, Dusart N, Kabouche I, Eycken E Alzheimers Dement. 2025; 21(2):e14530.

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Screening for early Alzheimer's disease: enhancing diagnosis with linguistic features and biomarkers.

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Automated remote speech-based testing of individuals with cognitive decline: Bayesian agreement of transcription accuracy.

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