Spoken dialogue systems have transformed human-machine interaction by providing real-time responses to queries. However, misunderstandings between the user and system persist. This study explores the significance of interactional language in dialogue repair between virtual assistants and users by analyzing interactions with Google Assistant and Siri, focusing on their utilization and response to the other-initiated repair strategy "huh?" prevalent in human-human interaction. Findings reveal several assistant-generated strategies but an inability to replicate human-like repair strategies such as "huh?". English and Spanish user acceptability surveys show differences in users' repair strategy preferences and assistant usage, with both similarities and disparities among the two surveyed languages. These results shed light on inequalities between interactional language in human-human interaction and human-machine interaction, underscoring the need for further research on the impact of interactional language in human-machine interaction in English and beyond.

It is one of the goals of this project to fill this gap by using theoretical models The goal of this talk is to introduce a systematic research agenda of language in interaction. Specifically, I propose to introduce a which aims to understand the nature of interaction between humans novel measure of comparison: the use of aspects of language that and artificial conversational agents (CA) (henceforth humanmachine are dedicated to regulating conversational interaction (henceforth interaction, HMI). Specifically, we shall take an explicit i-language).