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ESCoT: Towards Interpretable Emotional Support Dialogue Systems

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This is the repository of our ACL 2024 main paper "ESCoT: Towards Interpretable Emotional Support Dialogue Systems".

ESD-CoT Dataset

Our ESD-CoT dataset is organized under the data folder and is split into three JSON files: train, val, and test. Each file contains samples structured as follows:

{
    "id": ,
    "original_data": {
        "dialog": [
            {
                "speaker": "seeker",
                "content": "Hi, I'm having a really hard time managing my schoolwork and extracurricular activities. I feel like there's just not enough hours in the day."
            },
            ...
            {
                "speaker": "seeker",
                "content": "Yeah, I can try that."
            }
        ],
        "strategy": "Providing Suggestions",
        "response": "Great, and let's touch base next week to see if the list has been helpful. In the meantime, have you considered talking to your teacher or a guidance counselor about feeling overwhelmed?"
    },
    "cot_data": {
        "emotion": "The seeker feels overwhelmed and stretched thin.",
        "emotion_stimuli": "The seeker is struggling to manage schoolwork...",
        "individual_appraisal": "The seeker thinks they are not able to do anything well...",
        "recognized_strategy": "Providing Suggestions",
        "strategy_reason": "To address the seeker's feeling of being overwhelmed and..."
    }
}

Additionally, we provide instructional format training data in the data/ablation_data folder.

Model Training

Download the pretrained models

Download the LLAMA2-7B-CHAT model.

The training of LLAMA2-CHAT model is based on the SFT trainer of Transformer Reinforcement Learning.

Train Model

Run bash scripts/supervised_finetune_llama2_cot.sh to train your model.

Run bash scripts/supervised_finetune_llama2_cot_ablation.sh for Ablation Study model training.

Test Model

Run bash scripts/test_llama2_chat_sft_cot.sh or scripts/test_llama2_inference_cot.sh.

Cite

If you use our codes or your research is related to our work, please kindly cite our paper:

@inproceedings{zhang-etal-2024-escot,
    title = "{ESC}o{T}: Towards Interpretable Emotional Support Dialogue Systems",
    author = "Zhang, Tenggan and Zhang, Xinjie and Zhao, Jinming and Zhou, Li and Jin, Qin",
    booktitle = "Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    year = "2024"
}

Please contact zhangxinjie827@ruc.edu.cn for any problems.

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This is the repository of our ACL 2024 paper "ESCoT: Towards Interpretable Emotional Support Dialogue Systems".

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