# Sequential annotations for naturally-occurring HRI: first insights

arXiv: https://arxiv.org/abs/2308.15097 · HTML: https://mlsanity.com/paper/2308.15097/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 43 references that are in the map.
- First posted on arXiv 29 Aug 2023.

## Builds on (most cited first, 1 of 1)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)

## Abstract (arXiv)

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.