COSMIC: COmmonSense knowledge for eMotion Identification in Conversations

• URL: http://arxiv.org/abs/2010.02795v1
• Date: Tue, 6 Oct 2020 15:09:38 GMT
• Title: COSMIC: COmmonSense knowledge for eMotion Identification in Conversations
• Authors: Deepanway Ghosal, Navonil Majumder, Alexander Gelbukh, Rada Mihalcea, Soujanya Poria
• Abstract summary: We propose COSMIC, a new framework that incorporates different elements of commonsense such as mental states, events, and causal relations. We show that COSMIC achieves new state-of-the-art results for emotion recognition on four different benchmark conversational datasets.
• Score: 95.71018134363976
• License: http://creativecommons.org/licenses/by-sa/4.0/
• 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-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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