In recent years, the number of human-machine interactions has increased considerably. Additionally, we have evidence of linguistic differences between human-machine interactions and human–human conversations (e.g., Timpe-Laughlin et al., 2022). Therefore, it is reasonable to revisit theoretical frameworks that conceptualize interactional language use and investigate to what extent they still apply to technology-mediated interactions. As a first attempt at exploring whether pragmatics theories apply to human-machine interaction, we examined how well Kecskés's (2013) socio-cognitive approach (SCA) focusing on asymmetric interactions (e.g., between interlocutors of different language backgrounds) applies to the asymmetry of human-machine interactions.

Using examples from experimental data, we present the nature of common ground between human and machine (spoken dialogue system) interlocutors, focusing on the construction of and reliance on the emergent side of common ground that is informed by the actual situational experience. Like Kecskés, we argue that both egocentrism and cooperation play a role in human-machine interaction. While the former is manifested in approaching the machine interlocutor as if it was human, the latter appears to play a role in common ground seeking and building as well as in recipient design. We demonstrate that Kecskés's SCA is a fitting framework for analyzing human-machine communication contexts.

近年来，人机交互的数量显着增加。此外，我们有证据表明人机交互和人机对话之间存在语言差异（例如 Timpe-Laughlin 等人，2022）。因此，重新审视将交互语言使用概念化的理论框架并调查它们在多大程度上仍适用于技术介导的交互是合理的。作为探索语用学理论是否适用于人机交互的第一次尝试，我们检验了 Kecskés (2013) 关注不对称交互（例如，不同语言背景的对话者之间）的社会认知方法 (SCA) 如何适用于人机交互。

使用实验数据中的例子，我们展示了人类和机器（口语对话系统）对话者之间共同点的性质，重点是构建和依赖由实际情境经验告知的共同点的涌现面。像 Kecskés 一样，我们认为自我中心主义和合作都在人机交互中发挥作用。虽然前者表现在接近机器对话者，就好像它是人类一样，但后者似乎在寻求和建立共同点以及接受者设计中发挥作用。我们证明 Kecskés 的 SCA 是一个适合分析人机通信上下文的框架。