Turn-Level Empathy Prediction Using Psychological Indicators

Shaz Furniturewala, Kokil Jaidka
7/11/2024
cs.CL

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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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Cite this paper

@article{furniturewala2024turnlevel,
  title  = {Turn-Level Empathy Prediction Using Psychological Indicators},
  author = {Shaz Furniturewala and Kokil Jaidka},
  year   = {2024},
  eprint = {2407.08607},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2407.08607v1}
}

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