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.
Abstract (translated)
健康教练有助于患者识别和实现与生活方式相关的目标，有效改善慢性疾病控制并减轻心理健康状况。然而，由于其高度个性化和劳动密集的性质，健康教练的费用是不可承受的。在本文中，我们提出了一个与患者进行对话的系统，帮助他们创建和实现具体目标，并能够体谅他们的情感。然而，由于现实世界健康教练数据集有限，且情感表达微妙，因此我们提出了一个模块化健康教练对话系统，结合简化的NLU和NLG框架以及机制条件下的情感响应生成。通过自动和人类评估，我们证明了我们的系统生成更有同情心、流畅和连贯的回答，并在NLU任务上优于现有技术，同时需要更少的注释。我们认为，我们的方法是构建自动和更易访问的健康教练系统的关键一步。
URL
https://arxiv.org/abs/2404.08888
