论文标题
生成，评估和选择：与响应评估器的对话系统多样性感知响应生成
Generate, Evaluate, and Select: A Dialogue System with a Response Evaluator for Diversity-Aware Response Generation
论文作者
论文摘要
我们的目标是克服当前对话系统的响应中缺乏多样性，并开发作为对话伙伴参与的对话系统。我们提出了一个生成器评估器模型，该模型评估响应发生器生成的多个响应，并选择评估器的最佳响应。通过产生多种响应，我们获得了多种响应。我们进行人体评估，将提议系统的输出与基线系统的输出进行比较。人类评估的结果表明，拟议系统的响应通常被认为比基线系统更好，并指示了所提出的方法的有效性。
We aim to overcome the lack of diversity in responses of current dialogue systems and to develop a dialogue system that is engaging as a conversational partner. We propose a generator-evaluator model that evaluates multiple responses generated by a response generator and selects the best response by an evaluator. By generating multiple responses, we obtain diverse responses. We conduct human evaluations to compare the output of the proposed system with that of a baseline system. The results of the human evaluations showed that the proposed system's responses were often judged to be better than the baseline system's, and indicated the effectiveness of the proposed method.
