A Taxonomy of Conceptual Alignment in Human-Robot Dialogue

2026-06-21

AI Summary

Human–robot dialogue often suffers from inefficiency due to a lack of shared understanding of conceptual meanings. This work reframes concept alignment as a bidirectional co-construction process and, for the first time from a design perspective, proposes a structured framework that integrates a systematic taxonomy with actionable dialogic behavior schemata. By synthesizing methods from conversation analysis, human–robot interaction design, and dialog act modeling, the study provides an analyzable, comparable, and reusable foundational toolkit for achieving concept alignment in human–robot interaction. This contribution advances both systematic design practices and empirical research in the field.

Abstract

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.

Problem

• conceptual alignment
• human-robot dialogue
• meaning coordination
• dialogue design
• interactive communication

Innovation

• conceptual alignment
• human-robot dialogue
• taxonomy
• dialogue act schema
• co-constructive process