Using Vocal Characteristics To Classify Psychological Distress in Adult Helpline Callers: Retrospective Observational Study.

ABSTRACT:

Background

Elevated psychological distress has demonstrated impacts on individuals' health. Reliable and efficient ways to detect distress are key to early intervention. Artificial intelligence has the potential to detect states of emotional distress in an accurate, efficient, and timely manner.

Objective

The aim of this study was to automatically classify short segments of speech obtained from callers to national suicide prevention helpline services according to high versus low psychological distress and using a range of vocal characteristics in combination with machine learning approaches.

Methods

A total of 120 telephone call recordings were initially converted to 16-bit pulse code modulation format. Short variable-length segments of each call were rated on psychol

SUBMITTER: Iyer R 

PROVIDER: S-EPMC9811648 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature