DAG-ERC

Pytorch code for ACL-IJCNLP 2021 accepted paper "Directed Acyclic Graph Network for Conversational Emotion Recognition"

Requirements

• Python 3.6
• PyTorch 1.6.0
• Transformers 3.5.1
• CUDA 10.1

Preparation

Datasets and Utterance Feature

You can download the dataset and extracted utterance feature from https://drive.google.com/file/d/1R5K_2PlZ3p3RFQ1Ycgmo3TgxvYBzptQG/view?usp=sharing or https://pan.baidu.com/s/1H_LXQbDCfbWlwG1KvzNW6Q 提取码 c9vk

Training

You can train the models with the following codes:

For IEMOCAP: python run.py --dataset IEMOCAP --gnn_layers 4 --lr 0.0005 --batch_size 16 --epochs 30 --dropout 0.2

For MELD: python run.py --dataset MELD --lr 0.00001 --batch_size 64 --epochs 70 --dropout 0.1

For DailyDialog: python run.py --dataset EmoryNLP --lr 0.00005 --batch_size 32 --epochs 100 --dropout 0.3

For EmoryNLP: python run.py --dataset DailyDialog --gnn_layers 3 --lr 0.00002 --batch_size 64 --epochs 50 --dropout 0.3