Summary of Towards Enhancing Health Coaching Dialogue in Low-resource Settings, by Yue Zhou et al.
Towards Enhancing Health Coaching Dialogue in Low-Resource Settings
by Yue Zhou, Barbara Di Eugenio, Brian Ziebart, Lisa Sharp, Bing Liu, Ben Gerber, Nikolaos Agadakos, Shweta Yadav
First submitted to arxiv on: 13 Apr 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed dialogue system converses with patients to help them set and achieve lifestyle-related goals, improving chronic disease management and mental wellbeing. The system combines simplified natural language understanding (NLU) and generation (NLG) frameworks with mechanism-conditioned empathetic response generation. Through automatic and human evaluation, the system outperforms state-of-the-art NLU tasks while requiring less annotation. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A dialogue system is being developed to help patients create and achieve health-related goals, which can improve chronic disease management and mental wellbeing. The goal is to make this type of coaching more accessible by using a simplified approach that requires less data to train. The system uses technology to understand and respond to patients in a way that’s empathetic and helpful. |
Keywords
* Artificial intelligence * Language understanding
