一种用于评估日常生活活动能力的对话系统：利用接地知识提升一致性
A Dialogue System for Assessing Activities of Daily Living: Improving Consistency with Grounded Knowledge
AI总结：
针对ADL评估中评估者专业水平不一导致的一致性问题，本文构建含NLU与NLG模块的对话系统，结合查询分类、个体背景知识和类InstructGPT模型生成一致回复。
摘要：
在医疗保健领域，自我照护能力体现在“日常生活活动（Activities of Daily Living，ADL）”中，ADL被用作衡量功能能力（功能状态）的指标。功能状态不足可能导致生活状况恶化，从而需要个人护理和协助。为准确识别需要支持的人，援助项目会持续评估参与者在多个领域的功能状态。然而，当涉及多名专业水平各异的评估人员时，评估过程可能出现一致性问题。尤其是新手评估人员，可能缺乏与参与者进行真实互动所需的准备。为解决这一问题，我们开发了一个对话系统，以自然且可复现的方式模拟评估人员与不同功能状态个体之间的互动。该对话系统由两个主要模块组成，分别用于自然语言理解（NLU）和自然语言生成（NLG）。为生成与底层知识库一致的回复，对话系统既需要理解用户查询，也需要理解被模拟个体的个人背景细节。为满足这一要求，我们进行了查询分类实验，并使用近期发布的若干类InstructGPT模型，基于这些个人背景细节生成回复。
英文摘要：
In healthcare, the ability to care for oneself is reflected in the "Activities of Daily Living (ADL)," which serve as a measure of functional ability (functioning). A lack of functioning may lead to poor living conditions requiring personal care and assistance. To accurately identify those in need of support, assistance programs continuously evaluate participants' functioning across various domains. However, the assessment process may encounter consistency issues when multiple assessors with varying levels of expertise are involved. Novice assessors, in particular, may lack the necessary preparation for real-world interactions with participants. To address this issue, we developed a dialogue system that simulates interactions between assessors and individuals of varying functioning in a natural and reproducible way. The dialogue system consists of two major modules, one for natural language understanding (NLU) and one for natural language generation (NLG), respectively. In order to generate responses consistent with the underlying knowledge base, the dialogue system requires both an understanding of the user's query and of biographical details of an individual being simulated. To fulfill this requirement, we experimented with query classification and generated responses based on those biographical details using some recently released InstructGPT-like models.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
