Existing emotion-aware conversational models usually focus on controlling the response contents to align with a specific emotion class, whereas empathy is the ability to understand and concern the feelings and experience of others. Hence, it is critical to learn the causes that evoke the users' emotion for empathetic responding, a.k.a. emotion causes. To gather emotion causes in online environments, we leverage counseling strategies and develop an empathetic chatbot to utilize the causal emotion information. On a real-world online dataset, we verify the effectiveness of the proposed approach by comparing our chatbot with several SOTA methods using automatic metrics, expert-based human judgements as well as user-based online evaluation.
翻译：现有的情感意识对话模式通常侧重于控制响应内容,使之与特定情感阶级一致,而同情感则是理解和关注他人感情和经验的能力。 因此,了解激发用户情感的原因至关重要。 要在网上环境中收集情感原因,我们利用咨询策略,开发一个同情性聊天机,以利用因果情感信息。在现实世界的在线数据集中,我们通过使用自动计量、专家人类判断和用户在线评价,将我们所提议方法与若干SOTA方法进行比较,从而核实拟议方法的有效性。
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