We present EmoBERTa: Speaker-Aware Emotion Recognition in Conversation with RoBERTa, a simple yet expressive scheme of solving the ERC (emotion recognition in conversation) task. By simply prepending speaker names to utterances and inserting separation tokens between the utterances in a dialogue, EmoBERTa can learn intra- and inter- speaker states and context to predict the emotion of a current speaker, in an end-to-end manner. Our experiments show that we reach a new state of the art on the two popular ERC datasets using a basic and straight-forward approach. We've open sourced our code and models at https://github.com/tae898/erc.
EmoBERTa: Speaker-Aware Emotion Recognition in Conversation with RoBERTa
EmoBERTa enhances emotion recognition in conversations by incorporating speaker information and context using RoBERTa, achieving new performance benchmarks with minimal modifications.
- Year
- 2021
- Venue
- arXiv 2021
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- 2
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- Abstract onlyARXIV-DEFAULT
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- arxiv.org/abs/2108.12009ARXIV-DEFAULT
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