Papers › A Discourse-Aware Graph Neural Network for Emotion Recognition in Multi-Party Conversation
A Discourse-Aware Graph Neural Network for Emotion Recognition in Multi-Party Conversation
Yang Sun, Nan Yu, Guohong Fu
Emotion recognition in multi-party conversation (ERMC) is becoming increasingly popular as an emerging research topic in natural language processing. Prior research focuses on exploring sequential information but ignores the discourse structures of conversations. In this paper, we investigate the importance of discourse structures in handling informative contextual cues and speaker-specific features for ERMC. To this end, we propose a discourse-aware graph neural network (ERMC-DisGCN) for ERMC. In particular, we design a relational convolution to lever the self-speaker dependency of interlocutors to propagate contextual information. Furthermore, we exploit a gated convolution to select more informative cues for ERMC from dependent utterances. The experimental results show our method outperforms multiple baselines, illustrating that discourse structures are of great value to ERMC.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Emotion Recognition in Conversation | EmoryNLP | ERMC-DisGCN | Weighted-F1 | 36.38 | #22 of 28 | Archive leaderboard | report |
| Emotion Recognition in Conversation | IEMOCAP | ERMC-DisGCN | Accuracy | 65.25 | #49 of 59 | Archive leaderboard | report |
| Emotion Recognition in Conversation | IEMOCAP | ERMC-DisGCN | Macro-F1 | 63.43 | #49 of 59 | Archive leaderboard | report |
| Emotion Recognition in Conversation | IEMOCAP | ERMC-DisGCN | Weighted-F1 | 64.18 | #49 of 59 | Archive leaderboard | report |
| Emotion Recognition in Conversation | MELD | ERMC-DisGCN | Weighted-F1 | 64.22 | #39 of 68 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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