ECERC

ECERC

<!-- markdownlint-disable first-line-h1 --> <!-- markdownlint-disable html --> <!-- markdownlint-disable no-duplicate-header --> <p align="center"> <a href="https://github.com/TAN-OpenLab/ECERC"><b>Official GitHub</b>👁️</a> <a href="https://github.com/zoltol/ECERC"><b>Personal GitHub</b>👁️</a> </p>

This repository contains the official implementation of our paper ECERC: Evidence-Cause Attention Network for Multi-Modal Emotion Recognition in Conversation, published at ACL 2025.

1. Requirements

The experiments were conducted on a Windows 10 operating system equipped with an NVIDIA A100 GPU (80GB). Further system specifications are provided in the accompanying OS_info.txt and requirement.yml files.

conda env create -f requirement.yml -n ecerc

2. Datasets

The benchmark datasets used in our paper are IEMOCAP and MELD. Due to copyright restrictions, we provide links to the preprocessed versions only. The original datasets can be downloaded from their respective official sources.

3. Evaluation

Please follow our official GitHub repository or my personal GitHub repository.

4. Citation

@inproceedings{zhang-tan-2025-ecerc,
    title = "{ECERC}: Evidence-Cause Attention Network for Multi-Modal Emotion Recognition in Conversation",
    author = "Zhang, Tao  and
      Tan, Zhenhua",
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.acl-long.102/",
    pages = "2064--2077",
    ISBN = "979-8-89176-251-0"
}

5. License

This code repository is licensed under the MIT License. ECERC supports commercial use.