English

EmoBERTa: Speaker-Aware Emotion Recognition in Conversation with RoBERTa

Computation and Language 2021-08-30 v1

Abstract

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.

Keywords

Cite

@article{arxiv.2108.12009,
  title  = {EmoBERTa: Speaker-Aware Emotion Recognition in Conversation with RoBERTa},
  author = {Taewoon Kim and Piek Vossen},
  journal= {arXiv preprint arXiv:2108.12009},
  year   = {2021}
}

Comments

4 pages, not including references and appendix

R2 v1 2026-06-24T05:27:15.914Z