@techreport{b859fbfb4a554f58ad75b2af440c5c71,
title = "Emoberta: Speaker-aware emotion recognition in conversation with Roberta",
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",
author = "Taewoon Kim and Piek Vossen",
year = "2021",
month = aug,
day = "26",
language = "English",
volume = "2021",
series = "Computing Research Repository - arXiv",
publisher = "Cornell University",
pages = "1--7",
type = "WorkingPaper",
institution = "Cornell University",
}
