COSMIC: COmmonSense knowledge for eMotion Identification in Conversations

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

arXiv · PDF · Open in the Atlas

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Abstract

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-theart 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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