Machine Learning Approach to Identifying Empathy Using the Vocals of Mental Health Helpline Counselors: Algorithm Development and Validation.

ABSTRACT:

Background

This research study aimed to detect the vocal features immersed in empathic counselor speech using samples of calls to a mental health helpline service.

Objective

This study aimed to produce an algorithm for the identification of empathy from these features, which could act as a training guide for counselors and conversational agents who need to transmit empathy in their vocals.

Methods

Two annotators with a psychology background and English heritage provided empathy ratings for 57 calls involving female counselors, as well as multiple short call segments within each of these calls. These ratings were found to be well-correlated between the 2 raters in a sample of 6 common calls. Using vocal feature extraction from call segments and statistical variable sel

SUBMITTER: Sanjeewa R 

PROVIDER: S-EPMC12017608 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature