English

Sequential annotations for naturally-occurring HRI: first insights

Artificial Intelligence 2023-08-30 v1 Computation and Language

Abstract

We explain the methodology we developed for improving the interactions accomplished by an embedded conversational agent, drawing from Conversation Analytic sequential and multimodal analysis. The use case is a Pepper robot that is expected to inform and orient users in a library. In order to propose and learn better interactive schema, we are creating a corpus of naturally-occurring interactions that will be made available to the community. To do so, we propose an annotation practice based on some theoretical underpinnings about the use of language and multimodal resources in human-robot interaction. CCS CONCEPTS \bullet Computing methodologies \rightarrow Discourse, dialogue and pragmatics; \bullet Human-centered computing \rightarrow Text input; HCI theory, concepts and models; Field studies.

Keywords

Cite

@article{arxiv.2308.15097,
  title  = {Sequential annotations for naturally-occurring HRI: first insights},
  author = {Lucien Tisserand and Frédéric Armetta and Heike Baldauf-Quilliatre and Antoine Bouquin and Salima Hassas and Mathieu Lefort},
  journal= {arXiv preprint arXiv:2308.15097},
  year   = {2023}
}

Comments

Peer-reviewed workshop paper accepted for the ''Human-Robot Conversational Interaction'' workshop that took place at the ''ACM/IEEE International Conference on Human-Robot Interaction'' 2023 Conference in Stockholm, Sweden

R2 v1 2026-06-28T12:07:02.110Z