Towards Enhancing Health Coaching Dialogue in Low-Resource Settings

• URL: http://arxiv.org/abs/2404.08888v1
• Date: Sat, 13 Apr 2024 03:23:15 GMT
• Title: Towards Enhancing Health Coaching Dialogue in Low-Resource Settings
• Authors: Yue Zhou, Barbara Di Eugenio, Brian Ziebart, Lisa Sharp, Bing Liu, Ben Gerber, Nikolaos Agadakos, Shweta Yadav,
• Abstract summary: We propose to build a dialogue system that converses with the patients, helps them create and accomplish specific goals, and can address their emotions with empathy. We show that our system generates more empathetic, fluent, and coherent responses and outperforms the state-of-the-art in NLU tasks while requiring less annotation.
• Score: 9.162202267521355
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Health coaching helps patients identify and accomplish lifestyle-related goals, effectively improving the control of chronic diseases and mitigating mental health conditions. However, health coaching is cost-prohibitive due to its highly personalized and labor-intensive nature. In this paper, we propose to build a dialogue system that converses with the patients, helps them create and accomplish specific goals, and can address their emotions with empathy. However, building such a system is challenging since real-world health coaching datasets are limited and empathy is subtle. Thus, we propose a modularized health coaching dialogue system with simplified NLU and NLG frameworks combined with mechanism-conditioned empathetic response generation. Through automatic and human evaluation, we show that our system generates more empathetic, fluent, and coherent responses and outperforms the state-of-the-art in NLU tasks while requiring less annotation. We view our approach as a key step towards building automated and more accessible health coaching systems.

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