提出人机对话中概念对齐的分类框架，助力更自然的交互设计。
A Taxonomy of Conceptual Alignment in Human-Robot Dialogue
- 从双向共建视角定义概念对齐，突破单向研究局限。
- 构建按触发源和理解层级划分的对话分类体系。
- 提供可操作的对话行为模式，便于设计与评估。
成功对话依赖于对话双方对概念意义的对齐，这对人机交互而言既具挑战性又至关重要。当前研究受限于术语解释不一及对设计空间的孤立、单向探索。本文主张以设计为中心的理解方式，将概念对齐视为双向且共同建构的过程。我们提出一个分类体系，根据对话启动原因和涉及的概念理解层次来刻画对齐对话。同时，引入对话行为模式作为操作工具，捕捉实现对齐的具体互动策略。这些贡献共同为分析、比较和设计人机交互中的概念对齐提供了结构化基础。
原文摘要 · Abstract (English)
Successful conversations require speakers to align on the meaning of concepts, a challenging but crucial task for human-robot interaction. Understanding the process of establishing such alignment is hindered by competing interpretations of the term and isolated, unidirectional investigations of its design space. This paper argues for a design-centric understanding of conceptual alignment as a bidirectional and co-constructive process. We introduce a taxonomy that characterizes conceptual alignment dialogues along what triggers its initiation and what level(s) of conceptual understanding it concerns. We further present a dialogue act schema as an operational tool that captures the interactional moves through which alignment is achieved. Together, these contributions provide a structured foundation for analyzing, comparing, and designing conceptual alignment in human-robot interaction.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。