  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.
