Abstract
Existing slow and labor-intensive processes to assess and disseminate performance-feedback in training health pro-fessionals in counseling techniques like Motivational Interviewing(MI) does not scale to meet the demands of mental health workforce. To automate this process we present ReadMI, a fully functional mobile-cloud computing based dialogue-assessment tool that harnesses latest advancements in automatic speech recognition and natural language processing to analyze MI trainee utterances in real-time and generate instantaneous feed-back. In this paper we present the design and development details of ReadMI prototype. We also present the validation results obtained by comparing ReadMI's performance with MI experts. Our results demonstrate that, by automatically generating feed-back and reducing training delay, ReadMI demonstrates strong potential to scale up MI training workflow.
| Original language | English |
|---|---|
| Title of host publication | International Conference on Electrical, Computer, and Energy Technologies, ICECET 2024 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9798350395914 |
| ISBN (Print) | 9798350395914 |
| DOIs | |
| State | Published - 2024 |
| Event | 4th IEEE International Conference on Electrical, Computer, and Energy Technologies, ICECET 2024 - Sydney, Australia Duration: Jul 25 2024 → Jul 27 2024 |
Conference
| Conference | 4th IEEE International Conference on Electrical, Computer, and Energy Technologies, ICECET 2024 |
|---|---|
| Country/Territory | Australia |
| City | Sydney |
| Period | 7/25/24 → 7/27/24 |
ASJC Scopus Subject Areas
- Artificial Intelligence
- Computer Science Applications
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
- Electrical and Electronic Engineering
Keywords
- Distributed Computing
- computer based learning
- natural language processing
- workforce training
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