SemEval-2024 任务 3：对话中的多模态情感原因分析
SemEval-2024 Task 3: Multimodal Emotion Cause Analysis in Conversations
AI总结：
本文介绍 SemEval-2024 Task 3，该任务面向对话情感原因分析，设置文本与多模态两个情感—原因配对抽取子任务，并基于143次注册、216次提交总结数据集、评估及参赛系统发现。
摘要：
理解情感的能力是类人人工智能的重要组成部分，因为情感会显著影响人类的认知、决策和社会互动。除了对话中的情感识别之外，识别对话中个体情感状态背后的潜在原因，在许多应用场景中也具有重要意义。我们组织了 SemEval-2024 Task 3，名为“对话中的多模态情感原因分析”，旨在从对话中抽取所有情感及其对应原因的配对。在不同模态设置下，该任务包含两个子任务：对话中的文本情感—原因配对抽取（TECPE）和对话中的多模态情感—原因配对抽取（MECPE）。该共享任务吸引了 143 次注册和 216 次成功提交。本文介绍任务、数据集和评估设置，总结顶尖队伍的系统，并讨论参与者的发现。
英文摘要：
The ability to understand emotions is an essential component of human-like artificial intelligence, as emotions greatly influence human cognition, decision making, and social interactions. In addition to emotion recognition in conversations, the task of identifying the potential causes behind an individual's emotional state in conversations, is of great importance in many application scenarios. We organize SemEval-2024 Task 3, named Multimodal Emotion Cause Analysis in Conversations, which aims at extracting all pairs of emotions and their corresponding causes from conversations. Under different modality settings, it consists of two subtasks: Textual Emotion-Cause Pair Extraction in Conversations (TECPE) and Multimodal Emotion-Cause Pair Extraction in Conversations (MECPE). The shared task has attracted 143 registrations and 216 successful submissions. In this paper, we introduce the task, dataset and evaluation settings, summarize the systems of the top teams, and discuss the findings of the participants.
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。
