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.

翻译：我们阐述了一种基于对话分析的顺序与多模态分析方法所开发的、用于改善嵌入式对话代理交互效果的实践方法。其用例为一台Pepper机器人，它被期望在图书馆中为用户提供信息与引导。为提出并学习更优的交互模式，我们正在构建一个自然发生的人机交互语料库，该语料库将向社区开放共享。为此，我们提出了一种基于语言与多模态资源在人机交互中运用的理论基础之上的标注实践方案。CCS概念 $\bullet$ 计算方法学 $\rightarrow$ 语篇、对话与语用学；$\bullet$ 以人为中心的计算 $\rightarrow$ 文本输入；人机交互理论、概念与模型；现场研究。