Imagine having a conversation where you and your friend are describing things to each other. As the conversation progresses, you start using more specific and refined words to refer to those things. This phenomenon, called referential coordination, has been studied in previous research, which indicated that interactive repair mechanisms in dialogue contribute to this convergence of language. However, these studies primarily focused on how others initiate repair during a conversation, neglecting the potential role of self-initiated repair. To explore this further, researchers conducted a computer-mediated maze task experiment. Participants communicated through a chat tool that transformed their private turn-revisions into public self-repairs visible to the other participant. Interestingly, participants who received these artificial self-repairs used more abstract and systematized referring expressions but performed worse at the task. This suggests that the act of self-repair prompted participants to invest more effort in resolving referential coordination problems, leading to better understanding and increased use of abstract language. The findings highlight the power of self-repair in communication, showing how it influences language development and coordination between individuals in conversations. For more details, check out the full article!

Abstract
When interlocutors repeatedly describe referents to each other, they rapidly converge on referring expressions which become increasingly systematized and abstract as the interaction progresses. Previous experimental research suggests that interactive repair mechanisms in dialogue underpin convergence. However, this research has so far only focused on the role of other-initiated repair and has not examined whether self-initiated repair might also play a role. To investigate this question, we report the results from a computer-mediated maze task experiment. In this task, participants communicate with each other via an experimental chat tool, which selectively transforms participants’ private turn-revisions into public self-repairs that are made visible to the other participant. For example, if a participant, A, types “On the top square,” and then before sending, A revises the turn to “On the top row,” the server automatically detects the revision and transforms the private turn-revisions into a public self-repair, for example, “On the top square umm I meant row.” Participants who received these transformed turns used more abstract and systematized referring expressions, but performed worse at the task. We argue that this is due to the artificial self-repairs causing participants to put more effort into diagnosing and resolving the referential coordination problems they face in the task, yielding better grounded spatial semantics and consequently increased use of abstract referring expressions.

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