A Taxonomy of Conceptual Alignment in Human-Robot Dialogue
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Abstract (arXiv)
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.
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References · 8
- 2024Position: Towards Bidirectional Human-AI Alignmentcited by 18
- 2021Learning Perceptual Concepts by Bootstrapping from Human Queriescited by 12
- 2024Grounding Language in Multi-Perspective Referential Communicationcited by 12
- 2023Aligning Robot and Human Representationscited by 11
- 2024Concept Alignmentcited by 10
- 2021Patterns for Representing Knowledge Graphs to Communicate Situational Knowledge of Service Robotscited by 7
- 2023Communicative Robot Signals: Presenting a New Typology for Human-Robot Interactioncited by 4
- 2023Interactive Acquisition of Fine-grained Visual Concepts by Exploiting Semantics of Generic Characterizations in Discoursecited by 3
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