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Turn-Level Empathy Prediction Using Psychological Indicators
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Abstract
For the WASSA 2024 Empathy and Personality Prediction Shared Task, we propose a novel turn-level empathy detection method that decomposes empathy into six psychological indicators: Emotional Language, Perspective-Taking, Sympathy and Compassion, Extroversion, Openness, and Agreeableness. A pipeline of text enrichment using a Large Language Model (LLM) followed by DeBERTA fine-tuning demonstrates a significant improvement in the Pearson Correlation Coefficient and F1 scores for empathy detection, highlighting the effectiveness of our approach. Our system officially ranked 7th at the CONV-turn track.
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Publication details
- DOI
- 10.48550/arxiv.2407.08607
- OpenAlex
- W4400611985
- Document type
- preprint
- Language
- EN
- Source
- arXiv (Cornell University)
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