Automated Evaluation Of Psychotherapy Skills Using Speech And Language Technologies
Nikolaos Flemotomos, Victor R. Martinez, Zhuohao Chen, Karan Singla,, Victor Ardulov, Raghuveer Peri, Derek D. Caperton, James Gibson, Michael J., Tanana, Panayiotis Georgiou, Jake Van Epps, Sarah P. Lord, Tad Hirsch, Zac E., Imel, David C. Atkins, Shrikanth Narayanan

TL;DR
This paper presents an automated speech and language analysis tool for evaluating psychotherapy sessions, specifically Motivational Interviewing, to improve training and quality assurance in mental health care.
Contribution
It introduces a novel automated system that assesses therapist skills from audio recordings, providing detailed feedback to enhance training and clinical outcomes.
Findings
System analyzed over 5,000 real-world recordings
Provided comprehensive feedback on session dynamics and language use
Demonstrated potential to augment therapist training and evaluation
Abstract
With the growing prevalence of psychological interventions, it is vital to have measures which rate the effectiveness of psychological care to assist in training, supervision, and quality assurance of services. Traditionally, quality assessment is addressed by human raters who evaluate recorded sessions along specific dimensions, often codified through constructs relevant to the approach and domain. This is however a cost-prohibitive and time-consuming method that leads to poor feasibility and limited use in real-world settings. To facilitate this process, we have developed an automated competency rating tool able to process the raw recorded audio of a session, analyzing who spoke when, what they said, and how the health professional used language to provide therapy. Focusing on a use case of a specific type of psychotherapy called Motivational Interviewing, our system gives…
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