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Cognitive-Inspired Conversational-Strategy Reasoner for Socially-Aware Agents

机译:认知激发社会知识代理的对话战略推理

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In this work we propose a novel module for a dialogue system that allows a conversational agent to utter phrases that do not just meet the system's task intentions, but also work towards achieving the system's social intentions. The module - a Social Reasoner - takes the task goals the system must achieve and decides the appropriate conversational style and strategy with which the dialogue system describes the information the user desires so as to boost the strength of the relationship between the user and system (rapport), and therefore the user's engagement and willingness to divulge the information the agent needs to efficiently and effectively achieve the user's goals. Our Social Reasoner is inspired both by analysis of empirical data of friends and stranger dyads engaged in a task, and by prior literature in fields as diverse as reasoning processes in cognitive and social psychology, decision-making, sociolinguistics and conversational analysis. Our experiments demonstrated that, when using the Social Reasoner in a Dialogue System, the rapport level between the user and system increases in more than 35% in comparison with those cases where no Social Reasoner is used.
机译:在这项工作中,我们提出了一种新颖的模块,用于对话系统,允许会话代理完全不仅符合系统任务意图的短语,而且还努力实现系统的社会意图。该模块 - 社会推理员 - 采用任务目标,系统必须实现和决定对话系统描述用户希望的信息的适当的会话风格和策略,以便提高用户和系统之间的关系的强度(Rapport ),因此,用户的参与和旨在泄露代理需要有效地达到用户的目标的信息。我们的社会理发师通过分析朋友和陌生人二进的经验数据来激发了一项任务的经验数据,并通过现有的领域的文学,作为认知和社会心理学的推理过程,决策,社会语言学和对话分析。我们的实验表明,在对话系统中使用社会推理员时,用户和系统之间的关系水平与使用没有使用社会推理员的情况相比,超过35%。

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