Previous research from our laboratory which examined the impact of interruptions on performance in a collaborative communication task, found that interruptions from a synthetic agent, occurring either at fixed or random intervals, had a more deleterious effect on task performance than when interruption timing was determined by a human participant monitoring the communication task (Peters, Romigh, Bradley, & Raj, 2017). These results suggest that interruption times initiated by the human interrupters were more appropriate than the machine-generated ones; however, post-hoc analyses revealed no relation between interruption timing and language information prior to the human interruptions. Given these conflicting results and the demonstrated role of language information in other communication interactions, we aim to identify which spoken language components most motivate human interruption decisions, utilizing methods borrowed from the turn-taking literature (De Ruiter, Mitterer, & Enfield, 2006). Results indicate that listeners leverage prosodic and lexical information in making interruption decisions.
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