Abstract
Confusion is a mental state that can be triggered in task-oriented interactions and which can if left unattended lead to boredom, frustration, or disengagement from the task at hand. Previous work has demonstrated that confusion can be detected in situated human-robot interactions from visual and auditory cues. Therefore, in the next step, we propose appropriate interaction structures in this study, which should be used to mitigate confusion. We motivate and describe this dialogue mechanism through an information state-style dialogue framework and policies, and also outline the approach we are taking to integrate such a meta-conversational goal alongside core task-oriented considerations in modern data-driven conversational techniques.
| Original language | English |
|---|---|
| Journal | SemDial |
| DOIs | |
| Publication status | Published - 2023 |
Keywords
- confusion
- task-oriented interactions
- human-robot interactions
- visual cues
- auditory cues
- dialogue framework
- meta-conversational goal
- data-driven conversational techniques
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