@inproceedings{5b5c3abf03b7400bbff9df42ad6e3851,
title = "NCUEE-NLP at WASSA 2023 Empathy, Emotion, and Personality Shared Task: Perceived Intensity Prediction Using Sentiment-Enhanced RoBERTa Transformers",
abstract = "This paper describes our proposed system design for the WASSA 2023 shared task 1. We propose a unified architecture of ensemble neural networks to integrate the original RoBERTa transformer with two sentiment-enhanced RoBERTa-Twitter and EmoBERTa models. For Track 1 at the speech-turn level, our best submission achieved an average Pearson correlation score of 0.7236, ranking fourth for empathy, emotion polarity and emotion intensity prediction. For Track 2 at the essay-level, our best submission obtained an average Pearson correlation score of 0.4178 for predicting empathy and distress scores, ranked first among all nine submissions.",
author = "Lin, {Tzu Mi} and Chang, {Jung Ying} and Lee, {Lung Hao}",
note = "Publisher Copyright: {\textcopyright} 2023 Association for Computational Linguistics.; 13th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2023 ; Conference date: 14-07-2023",
year = "2023",
language = "???core.languages.en_GB???",
series = "Proceedings of the Annual Meeting of the Association for Computational Linguistics",
publisher = "Association for Computational Linguistics (ACL)",
pages = "548--552",
editor = "Jeremy Barnes and {De Clercq}, Orphee and Roman Klinger",
booktitle = "WASSA 2023 - 13th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop",
}