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Intensional Summaries as Cooperative Responses in Dialogue:Automation and Evaluation

机译:内涵摘要作为对话中的合作响应:自动化和评估

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摘要

Despite its long history, and a great deal of research producing many useful algorithms and observations, research in cooperative response generation has had little impact on the recent commercialization of dialogue technologies, particularly within the spoken dialogue community. We hypothesize that a particular type of cooperative response, intensional summaries, are effective for when users are unfamiliar with the domain. We evaluate this hypothesis with two experiments with CRUISER, a DS for in-car or mobile users to access restaurant information. First, we compare CRUISER with a baseline system-initiative DS, and show that users prefer cruiser. Then, we experiment with four algorithms for constructing intensional summaries in CRUISER, and show that two summary types are equally effective: summaries that maximize domain coverage and summaries that maximize utility with respect to a user model.
机译:尽管其历史悠久,并且进行了大量的研究,产生了许多有用的算法和观察结果,但是合作响应生成方面的研究对对话技术的最新商业化影响不大,尤其是在口头对话社区中。我们假设一种特殊类型的协作响应,即内涵摘要,对于用户不熟悉该域的情况是有效的。我们通过两个CRUISER实验对这一假设进行了评估,CRUISER是一个DS车载或移动用户访问餐厅信息的DS。首先,我们将CRUISER与基准系统启动DS进行比较,并表明用户更喜欢巡洋舰。然后,我们尝试了四种在CRUISER中构造内涵摘要的算法,并证明了两种摘要类型是同等有效的:最大化域覆盖范围的摘要和最大化针对用户模型的效用的摘要。

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