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arXiv 2010.02795cs.CL

COSMIC: COmmonSense knowledge for eMotion Identification in Conversations

University of Michigan(密歇根大学);Singapore University of Technology and Design(新加坡科技设计大学);CIC, Instituto Politécnico Nacional(墨西哥国立理工学院计算研究中心)

Deepanway Ghosal, Navonil Majumder, Alexander Gelbukh, Rada Mihalcea, Soujanya Poria

英文摘要:

In this paper, we address the task of utterance level emotion recognition in conversations using commonsense knowledge. We propose COSMIC, a new framework that incorporates different elements of commonsense such as mental states, events, and causal relations, and build upon them to learn interactions between interlocutors participating in a conversation. Current state-of-the-art methods often encounter difficulties in context propagation, emotion shift detection, and differentiating between related emotion classes. By learning distinct commonsense representations, COSMIC addresses these challenges and achieves new state-of-the-art results for emotion recognition on four different benchmark conversational datasets. Our code is available at https://github.com/declare-lab/conv-emotion.

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