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Effective applications of task-oriented dialogue agents are yet limited to simple tasks. One of the reasons behind could be that agents couldn’t “understand” more complicated requests due to failures in communicative grounding attempts, which establishes mutually agreed upon knowledge. Distinct from researches that evaluate dialogue agents’ performance using the rates of successfully completed tasks, this paper takes the linguistic approach of discourse analysis and investigates practical differences in how human and interlocutors make use of language to reach common ground in human-human and human-agent (Siri) dialogues given same tasks. Utilising the Degrees of Grounding model (Roque and Traum, 2008), the paper suggests how Siri’s dispreferred signal in expressing groundedness hindered accurate indication of whether the information is grounded. Interpretations with the modified incremental semantic processing models (Eshghi et al., 2015) suggests the exact point of breakdown in grounding, as well as the discrepancies in how updates of information were perceived by human and agent interlocutors. The paper suggested four major weaknesses in Siri: uninformative request repair, greedy use of grounding evidence, difficulties in interpreting resubmit and inability to understand human grounding strategies. Apart from the surface distinct language use, findings hinted a deeper challenge in optimising agents’ presentation and image to help adjust anticipated replies. In view of Siri’s vague and greedy expressions that misled users about its perceptions, the paper suggests a number of mitigation strategies, including increasing accuracy and informativity in agents’ delivery to help users adapt to their language style as how humans do with second-language speakers.
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