对话中同理心对齐的建模
Modeling Empathetic Alignment in Conversation
AI总结：
本文基于评价理论提出识别对话中同理心对齐的新方法，并构建了包含评价与对齐标注的新数据集，实验表明该方法可准确识别对齐，且心理健康专业人员表现出更高的同理心对齐。
摘要：
同理心需要换位思考：同理心回应要求一个人推理他人经历了什么，并用语言传达这种理解。然而，大多数关于同理心的自然语言处理方法并未明确建模这一对齐过程。在此，我们引入一种基于评价理论的新方法，用于识别同理心言语中的对齐。我们引入一个新数据集，包含超过9.2K条对一个人经历的不同类型评价的跨度级标注，以及超过3K条说话者与观察者言语之间的同理心对齐标注。通过计算实验，我们表明这些评价和对齐可以被准确识别。在超过9.2M个Reddit对话的实验中，我们发现评价捕捉到了有意义的行为分组，但大多数回应只有极少的对齐。然而，我们发现心理健康专业人员参与的同理心对齐程度显著更高。
英文摘要：
Empathy requires perspective-taking: empathetic responses require a person to reason about what another has experienced and communicate that understanding in language. However, most NLP approaches to empathy do not explicitly model this alignment process. Here, we introduce a new approach to recognizing alignment in empathetic speech, grounded in Appraisal Theory. We introduce a new dataset of over 9.2K span-level annotations of different types of appraisals of a person's experience and over 3K empathetic alignments between a speaker's and observer's speech. Through computational experiments, we show that these appraisals and alignments can be accurately recognized. In experiments in over 9.2M Reddit conversations, we find that appraisals capture meaningful groupings of behavior but that most responses have minimal alignment. However, we find that mental health professionals engage with substantially more empathetic alignment.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
