Papers with COntext-Dependent Encoder
Exploiting Unsupervised Data for Emotion Recognition in Conversations (2020.findings-emnlp)
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| Challenge: | Existing models for Emotion Recognition in Conversations lack supervised data, which prevents them from playing their maximum effect. |
| Approach: | They propose a Conversation Completion task which uses unsupervised conversation data to leverage unsupervised data. |
| Outcome: | The proposed model improves on the minority emotion classes on the ERC datasets. |