论文标题
个人叙事的情感载体认可
Emotion Carrier Recognition from Personal Narratives
论文作者
论文摘要
个人叙事（PN） - 从自己的经验中对事实，事件和思想的回忆 - 经常在日常对话中使用。到目前为止，PN主要是针对价预测或情感分类（例如快乐，悲伤）探索的。但是，这些任务可能会忽略更细粒度的信息，这些信息可能与理解PN相关。在这项工作中，我们提出了一项叙事理解的新任务：情感载体识别（ECR）。情感载体，带有叙述者情绪的文字片段（例如失去爷爷，高中聚会），提供了对情绪状态的细粒度描述。我们在用情感载体注释的PNS语料库中探索ECR的任务，并研究该任务的不同机器学习模型。我们建议对ECR的评估策略，包括适合不同任务的指标。
Personal Narratives (PN) - recollections of facts, events, and thoughts from one's own experience - are often used in everyday conversations. So far, PNs have mainly been explored for tasks such as valence prediction or emotion classification (e.g. happy, sad). However, these tasks might overlook more fine-grained information that could prove to be relevant for understanding PNs. In this work, we propose a novel task for Narrative Understanding: Emotion Carrier Recognition (ECR). Emotion carriers, the text fragments that carry the emotions of the narrator (e.g. loss of a grandpa, high school reunion), provide a fine-grained description of the emotion state. We explore the task of ECR in a corpus of PNs manually annotated with emotion carriers and investigate different machine learning models for the task. We propose evaluation strategies for ECR including metrics that can be appropriate for different tasks.
