Automatic speech analysis for detecting cognitive decline of older adults.

ABSTRACT:

Background

Speech analysis has been expected to help as a screening tool for early detection of Alzheimer's disease (AD) and mild-cognitively impairment (MCI). Acoustic features and linguistic features are usually used in speech analysis. However, no studies have yet determined which type of features provides better screening effectiveness, especially in the large aging population of China.

Objective

Firstly, to compare the screening effectiveness of acoustic features, linguistic features, and their combination using the same dataset. Secondly, to develop Chinese automated diagnosis model using self-collected natural discourse data obtained from native Chinese speakers.

Methods

A total of 92 participants from communities in Shanghai, completed MoCA-B and a picture des

SUBMITTER: Huang L 

PROVIDER: S-EPMC11338907 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature