Effective Context Modeling Framework for Emotion Recognition in Conversations

Table of Contents

• Introduction
• Installation
• Usage
• Acknowledgement
• Citation

Introduction

This is the official implementation of the paper "Effective Context Modeling Framework for Emotion Recognition in Conversations". Our paper is published at ICASSP 2025 🎉.

Figure: Detailed architecture of (A) the proposed ConxGNN, (B) Inception Graph Block, and (C) HyperBlock.

Installation

Install the dependencies:

 conda env create -f environment/environment.yml

Read environment/helper.txt if some libraries can't be installed.

Usage

To train the model, run the following command:

python train.py configs/meld.yaml       # for MELD
python train.py configs/iemocap6.yaml   # for IEMOCAP

Acknowledgement

Part of the code is borrowed from the following repositories. We would like to thank the authors for their great work.

• MultiEMO
• M3Net
• CORECT

Citation

If you find this work helpful, please consider citing our paper:

@misc{van2024effectivecontextmodelingframework,
      title={Effective Context Modeling Framework for Emotion Recognition in Conversations}, 
      author={Cuong Tran Van and Thanh V. T. Tran and Van Nguyen and Truong Son Hy},
      year={2024},
      eprint={2412.16444},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2412.16444}, 
}