NCUEE-NLP at WASSA 2023 Empathy, Emotion, and Personality Shared Task: Perceived Intensity Prediction Using Sentiment-Enhanced RoBERTa Transformers

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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.

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APA

Lin, T. M., Chang, J. Y., & Lee, L. H. (2023). NCUEE-NLP at WASSA 2023 Empathy, Emotion, and Personality Shared Task: Perceived Intensity Prediction Using Sentiment-Enhanced RoBERTa Transformers. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 548–552). Association for Computational Linguistics (ACL).

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