Correlating natural language processing and automated speech analysis with clinician assessment to quantify speech-language changes in mild cognitive impairment and Alzheimer's dementia.

ABSTRACT:

Background

Language impairment is an important marker of neurodegenerative disorders. Despite this, there is no universal system of terminology used to describe these impairments and large inter-rater variability can exist between clinicians assessing language. The use of natural language processing (NLP) and automated speech analysis (ASA) is emerging as a novel and potentially more objective method to assess language in individuals with mild cognitive impairment (MCI) and Alzheimer's dementia (AD). No studies have analyzed how variables extracted through NLP and ASA might also be correlated to language impairments identified by a clinician.

Methods

Audio recordings (n=30) from participants with AD, MCI, and controls were rated by clinicians for word-finding difficulty, inc

SUBMITTER: Yeung A 

PROVIDER: S-EPMC8178861 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature