Conversation requires a substantial amount of coordination between dialogue participants, from managing turn taking to negotiating mutual understanding. Part of this coordination effort surfaces as the reuse of linguistic behaviour across speakers, a process often referred to as alignment. While the presence of linguistic alignment is well documented in the literature, several questions remain open, including the extent to which patterns of reuse across speakers have an impact on the emergence of labelling conventions for novel referents. In this study, we put forward a methodology for automatically detecting shared lemmatised constructions -- expressions with a common lexical core used by both speakers within a dialogue -- and apply it to a referential communication corpus where participants aim to identify novel objects for which no established labels exist. Our analyses uncover the usage patterns of shared constructions in interaction and reveal that features such as their frequency and the amount of different constructions used for a referent are associated with the degree of object labelling convergence the participants exhibit after social interaction. More generally, the present study shows that automatically detected shared constructions offer a useful level of analysis to investigate the dynamics of reference negotiation in dialogue.

翻译：对话需要参与者之间进行大量的协调，从话题轮换管理到相互理解的协商。这种协调努力的部分体现为说话人之间语言行为的复现，这一过程常被称为对齐。尽管语言对齐的存在在文献中已有充分记载，但仍存若干待解决问题，包括跨说话人的复现模式在多大程度上影响新型指称对象标签约定的形成。本研究提出了一种自动检测共享词形规范化结构（即在对话中双方均使用的具有共同词汇核心的表达方式）的方法，并将其应用于一个指称交流语料库——在该语料中，参与者需识别尚未建立既定标签的新奇物体。我们的分析揭示了互动过程中共享结构的使用模式，并发现其使用频率及对某一指称对象所使用的不同结构数量等特征，与参与者社交互动后展示的物体标签趋同程度相关。更广泛而言，本研究显示，自动检测的共享结构为研究对话中指称协商的动态过程提供了有效的分析层面。