Hypergraph Neural Network for Emotion Recognition in Conversations
Authors: 
Cheng Zheng, Haojie Xu, Xiao SunAuthors Info & Claims
Cheng Zheng, Haojie Xu, Xiao SunAuthors Info & ClaimsArticle No.: 21, Pages 1 - 16
Abstract
Modeling conversational context is an essential step for emotion recognition in conversations. Existing works still suffer from insufficient utilization of local context information and remote context information. This article designs a hypergraph neural network, namely HNN-ERC, to better utilize local and remote contextual information. HNN-ERC combines the recurrent neural network with the conventional hypergraph neural network to strengthen connections between utterances and make each utterance receive information from other utterances better. The proposed model has empirically achieved state-of-the-art results on three benchmark datasets, demonstrating the effectiveness and superiority of the new model.
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- Hypergraph Neural Network for Emotion Recognition in Conversations
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February 2024
340 pages
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Publication History
Published: 08 February 2024
Online AM: 27 December 2023
Accepted: 20 December 2023
Revised: 27 May 2023
Received: 17 August 2022
Published in TALLIP Volume 23, Issue 2
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- Key Research and Development Program of Anhui Province
- National Key R&D Programme of China
- Major Project of Anhui Province
- General Programmer of the National Natural Science Foundation of China
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