Automatic Prosodic Analysis to Identify Mild Dementia

Abstract EN

This paper describes an exploratory technique to identify mild dementia by assessing the degree of speech deficits.

A total of twenty participants were used for this experiment, ten patients with a diagnosis of mild dementia and ten participants like healthy control.

The audio session for each subject was recorded following a methodology developed for the present study.

Prosodic features in patients with mild dementia and healthy elderly controls were measured using automatic prosodic analysis on a reading task.

A novel method was carried out to gather twelve prosodic features over speech samples.

The best classification rate achieved was of 85% accuracy using four prosodic features.

The results attained show that the proposed computational speech analysis offers a viable alternative for automatic identification of dementia features in elderly adults.