Personal assistants using a command-dialogue model of speech recognition, such as Siri and Cortana, have become increasingly powerful and popular for individual use. In this paper we explore whether similar techniques could be used to create a speech-based agent system which, in a group meeting setting, would similarly monitor spoken dialogue, pro-actively detect useful actions, and carry out those actions without specific commands being spoken. Using a low-fi technical probe, we investigated how such a system might perform in the collaborative work setting and how users might respond to it. We recorded and transcribed a varied set of nine meetings from which we generated simulated lists of automated \u2018action items\u2019, which we then asked the meeting participants to review retrospectively. The low rankings given on these discovered items are suggestive of the difficulty in applying personal assistant technology to the group setting, and we document the issues emerging from the study. Through observations, we explored the nature of meetings and the challenges they present for speech agents. <\/p>\n","protected":false},"excerpt":{"rendered":"
Personal assistants using a command-dialogue model of speech recognition, such as Siri and Cortana, have become increasingly powerful and popular for individual use. In this paper we explore whether similar techniques could be used to create a speech-based agent system which, in a group meeting setting, would similarly monitor spoken dialogue, pro-actively detect useful actions, 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