2020/10/06 by Deepanway Ghosal, Navonil Majumder, Ghosal, Deepanway +7 · 7 citations
Computer Science · Psychology · #Artificial intelligence #Benchmark (surveying) #Code (set theory) #Cognitive science #Commonsense knowledge #Commonsense reasoning #Communication #Computation and Language (cs.CL) #Computer science #Context (archaeology) #Conversation #Emotion and Mood Recognition #Emotion recognition #FOS: Computer and information sciences #Identification (biology) #Knowledge base #Mental state #Natural language processing #Psychology #Sentiment Analysis and Opinion Mining #Task (project management) #Topic Modeling #Utterance #cs.CL
paper · pdf · doi:10.48550/arxiv.2010.02795
published in arXiv (Cornell University) (Cornell University)
arxiv created 2020/10/06 · openalex publication_date 2020/10/06 · arxiv updated 2020/10/07 · openalex created_date 2022/07/25 · openalex updated_date 2026/08/08
In this paper, we address the task of utterance level emotion recognition in\nconversations using commonsense knowledge. We propose COSMIC, a new framework\nthat incorporates different elements of commonsense such as mental states,\nevents, and causal relations, and build upon them to learn interactions between\ninterlocutors participating in a conversation. Current state-of-the-art methods\noften encounter difficulties in context propagation, emotion shift detection,\nand differentiating between related emotion classes. By learning distinct\ncommonsense representations, COSMIC addresses these challenges and achieves new\nstate-of-the-art results for emotion recognition on four different benchmark\nconversational datasets. Our code is available at\nhttps://github.com/declare-lab/conv-emotion.\n