Observational coding of audio-video recordings of patient-therapist interactions is a key part of understanding the process and treatment adherence of psychotherapy interventions. In this collaborative project with researchers at U Washington and at UC Irvine, we plan to create and use advances in computational speech and spoken language processing to offer tools and methods for automating aspects of observational coding.

The specific theoretical framework for this project is based on Motivational Interviewing (MI). The focus of this BSP/BI effort is based on automating behavioral coding related to MI, namely the Motivational Interviewing Skills Code (MISC) and its derivative, the Motivational Interviewing Treatment Integrity (MITI) coding.

Sponsored Project:

Automating Behavioral Coding via Text-Mining and Speech Signal Processing

Sponsor:

NIH/National Institute on Alcohol Abuse and Alcoholism (NIAAA).
Collaboration between U Washington, UC Irvine, and USC.