cSCAN Rounds

Clarifying intentions in dialogue: miscommunication drives abstraction

One of the most contentious debates in studies of dialogue concerns the explanatory role assigned to speakers‘ intentions. To address this issue, this talk reports a computer-mediated variant of the maze task (Pickering & Garrod, 2004), which manipulates the dialogue by inserting artificial clarification requests that appear, to participants, as if they originate from each other. Two kinds of clarification were introduced: (1) Artificial "Why?" questions that query participants' intentions behind their utterance (2) Fragment clarification requests that repeat a single word from the prior turn, querying the content of participants' referring expressions. During the dialogue, as coordination develops, "Why?" clarification requests become progressively easier to respond to, while for fragment clarification requests the converse is the case. Further, fragment clarification requests that are introduced at the start of the interaction lead to interlocutors aligning quicker on more abstract and systematic referring expressions. Participants who receive these fragment clarification requests also converge quicker than participants in a baseline condition who received no interventions. This talk argues that this differential pattern is due to the interplay between two kinds of coordination problem. First, interlocutors must coordinate on the semantics of their referrring expressions. Second, interlocutors are also faced with the procedural coordination problem of managing the timing and sequencing of their contributions. This talk argues that both kinds of coordination are primarily driven by negative evidence of understanding; problem detection and resolution drives convergence.