The official implementation for the conference of the EMNLP 2023 paper A Training-Free Debiasing Framework with Counterfactual Reasoning for Conversational Emotion Detection.
- Python 3.9
- PyTorch 1.10.1
- Transformers 4.33.1
- CUDA 10.2
- pysentiment 0.2
Download multimodal-datasets and save it in ./multimodal-datasets.
python train-erc-text.pyuse train-erc-text.yaml to change the parameters.
If you find our work useful for your research, please kindly cite our paper as follows:
@inproceedings{tu2023training,
title={A Training-Free Debiasing Framework with Counterfactual Reasoning for Conversational Emotion Detection},
author={Tu, Geng and Jing, Ran and Liang, Bin and Yang, Min and Wong, Kam-Fai and Xu, Ruifeng},
booktitle={Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing},
pages={15639--15650},
year={2023}
}
The code of this repository partly relies on EmoBERTa and CORSAIR. I would like to show my sincere gratitude to the authors behind these contributions.