CUEMPATHY: A Counseling Speech Dataset for Psychotherapy Research

Fuente: arXiv
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Main Authors: Tao, Dehua, Chui, Harold, Luk, Sarah, Lee, Tan
Format: Preprint
Published: 2024
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author Tao, Dehua
Chui, Harold
Luk, Sarah
Lee, Tan
author_facet Tao, Dehua
Chui, Harold
Luk, Sarah
Lee, Tan
contents Psychotherapy or counseling is typically conducted through spoken conversation between a therapist and a client. Analyzing the speech characteristics of psychotherapeutic interactions can help understand the factors associated with effective psychotherapy. This paper introduces CUEMPATHY, a large-scale speech dataset collected from actual counseling sessions. The dataset consists of 156 counseling sessions involving 39 therapist-client dyads. The process of speech data collection, subjective ratings (one observer and two client ratings), and transcription are described. An automatic speech and text processing system is developed to locate the time stamps of speaker turns in each session. Examining the relationships among the three subjective ratings suggests that observer and client ratings have no significant correlation, while the client-rated measures are significantly correlated. The intensity similarity between the therapist and the client, measured by the averaged absolute difference of speaker-turn-level intensities, is associated with the psychotherapy outcomes. Recent studies on the acoustic and linguistic characteristics of the CUEMPATHY are introduced.
format Preprint
id arxiv_https___arxiv_org_abs_2409_02466
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle CUEMPATHY: A Counseling Speech Dataset for Psychotherapy Research
Tao, Dehua
Chui, Harold
Luk, Sarah
Lee, Tan
Audio and Speech Processing
Sound
Psychotherapy or counseling is typically conducted through spoken conversation between a therapist and a client. Analyzing the speech characteristics of psychotherapeutic interactions can help understand the factors associated with effective psychotherapy. This paper introduces CUEMPATHY, a large-scale speech dataset collected from actual counseling sessions. The dataset consists of 156 counseling sessions involving 39 therapist-client dyads. The process of speech data collection, subjective ratings (one observer and two client ratings), and transcription are described. An automatic speech and text processing system is developed to locate the time stamps of speaker turns in each session. Examining the relationships among the three subjective ratings suggests that observer and client ratings have no significant correlation, while the client-rated measures are significantly correlated. The intensity similarity between the therapist and the client, measured by the averaged absolute difference of speaker-turn-level intensities, is associated with the psychotherapy outcomes. Recent studies on the acoustic and linguistic characteristics of the CUEMPATHY are introduced.
title CUEMPATHY: A Counseling Speech Dataset for Psychotherapy Research
topic Audio and Speech Processing
Sound
url https://arxiv.org/abs/2409.02466