Turn-Level Empathy Prediction Using Psychological Indicators
<|reference_start|>Turn-Level Empathy Prediction Using Psychological Indicators: 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.<|reference_end|>
@article{furniturewala2024turn-level,
    title={Turn-Level Empathy Prediction Using Psychological Indicators},
    author={Shaz Furniturewala, Kokil Jaidka},
    journal={arXiv preprint arXiv:2407.08607},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.08607},
    primaryClass={cs.CL}
}