The code for ACL2023 paper: 《DualGATs: Dual Graph Attention Networks for Emotion Recognition in Conversations》
With Anaconda, we can create the environment with the provided environment.yml
:
conda env create --file environment.yml
conda activate MMERC
The code has been tested on Ubuntu 16.04 using a single GPU.
# For IEMOCAP:
CUDA_VISIBLE_DEVICES=0 python main.py --dataset IEMOCAP --lr 1e-4 --dropout 0.2 --batch_size 16 --gnn_layers 2
# For MELD:
CUDA_VISIBLE_DEVICES=0 python main.py --dataset MELD --lr 1e-4 --dropout 0.3 --batch_size 32 --gnn_layers 2
# For EmoryNLP:
CUDA_VISIBLE_DEVICES=0 python main.py --dataset EmoryNLP --lr 1e-4 --dropout 0.1 --batch_size 32 --gnn_layers 2
# For DailyDialog:
CUDA_VISIBLE_DEVICES=0 python main.py --dataset DailyDialog --lr 5e-5 --dropout 0.4 --batch_size 64 --gnn_layers 3
@inproceedings{zhang2023dualgats,
title={DualGATs: Dual Graph Attention Networks for Emotion Recognition in Conversations},
author={Zhang, Duzhen and Chen, Feilong and Chen, Xiuyi},
booktitle={Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
pages={7395--7408},
year={2023}
}