Papers by Jaeyeol Jeon

1 papers
Dimensional Emotion Detection from Categorical Emotion (2021.emnlp-main)

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Challenge: Using a model to predict fine-grained emotions along the continuous dimensions of valence, arousal, and dominance (VAD) with a corpus with categorical emotion annotations, we show that our approach reaches comparable performance to that of the state-of-the-art classifiers in categorial emotion classification and shows significant positive correlations with the ground truth VAD scores.
Approach: They propose to train a model to predict fine-grained emotions along the continuous dimensions of valence, arousal, and dominance with a corpus with categorical emotion annotations.
Outcome: The proposed model can predict emotions along the continuous dimensions of valence, arousal, and dominance (VAD) with a corpus with categorical emotion annotations.

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