CauAIN

• Code for IJCAI 2022 accepted paper titled "CauAIN: Causal Aware Interaction Network for Emotion Recognition in Conversations"
• Weixiang Zhao, Yanyan Zhao, Xin Lu.

Requirements

• Python 3.7
• PyTorch 1.8.2
• Transformers 4.12.3
• CUDA 11.1

Preparation

Commonsense Feature Generation with COMET

To extract COMET commonsense features, first download the required files from here. Keep the atomic_pretrained_model.pickle in comet/pretrained_models/ and the other pickle file in comet/data/atomic/processed/generation/. Then you can extract commonesnse features for all the datasets using

cd feature-extraction
python comet_feature_extract_all.py

Datasets, Utterance Feature and Commonsense Feature

You can download the dataset, extracted utterance feature and commonsense feature we used from: https://pan.baidu.com/s/1hNuUgUmjdOOQ1cqT75n-ZA 提取码:nwqa

or: https://drive.google.com/drive/folders/1--yCEESJ1TMReiiiWwTlnNL7H1p-erfq?usp=sharing

and place them into the corresponding folds like iemocap, dailydialog and meld

Training

You can train the models with the following codes:

For IEMOCAP:

python train_iemocap.py

For MELD:

python train_meld.py

For DailyDialog:

python train_dailydialog.py

Citation

If you find our work useful for your research, please kindly cite our paper as follows:

@inproceedings{CauAIN2022,
  author={Weixiang Zhao, Yanyan Zhao and Xin Lu},
  title     = {CauAIN: Causal Aware Interaction Network for Emotion Recognition in Conversations},
  booktitle = {Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, {IJCAI} 2022, Vienna, Austria, 23-29 July 2022},
  year      = {2022},
}