Abstract

Text-based computational approaches for assessing the quality of psychotherapy are being developed to support quality assurance and clinical training. However, due to the long durations of typical conversation based therapy sessions, and due to limited annotated modeling resources, computational methods largely rely on frequency-based lexical features or dialogue acts to assess the overall session level characteristics. In this work, we propose a hierarchical framework to automatically evaluate the quality of transcribed Cognitive Behavioral Therapy (CBT) interactions. Given the richly dynamic nature of the spoken dialog within a talk therapy session, to evaluate the overall session level quality, we propose to consider modeling it as a function of local variations across the interaction. To implement that empirically, we divide each psychotherapy session into conversation segments and initialize the segment-level …

Date

September 1, 2022

Authors

Zhuohao Chen, Nikolaos Flemotomos, Karan Singla, Torrey A Creed, David C Atkins, Shrikanth Narayanan

Journal

Computer speech & language

Volume

75

Pages

101380

Publisher

Academic Press