• To support future research, we release FailedESConv.json, 276 negative samples of emotional support conversations that were primarily dropped when we were collecting ESConv.
  • Our rule to determine an effectively negative sample: (# of turn > 2 AND # of speaker > 1) AND ((post-conversation survey was done AND (negative emotion intensity does not decrease OR empathy score <=2 OR relevance score <=2 )) OR (the support-seeker did not finish the post-conversation survey AND the support-seeker's last feedback score <= 2) )

Data and codes for the ACL 2021 paper: Towards Emotional Support Dialog Systems

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

@inproceedings{liu-etal-2021-towards,
  title={Towards Emotional Support Dialog Systems},
  author={Liu, Siyang  and 
    Zheng, Chujie  and 
    Demasi, Orianna  and 
    Sabour, Sahand  and 
    Li, Yu  and 
    Yu, Zhou  and 
    Jiang, Yong  and 
    Huang, Minlie},
  booktitle={ACL},
  year={2021}
}

The corpus file is ESConv.json. We have collected more conversations with more problem topics. ESConv now contains 1,300 conversations with 10 topic problems.

* denotes the new topics added during the second collection. We hope new data supports the future research in transferring the ability of models from old topics to new ones.

We provide two versions of model implementation:

• codes is the version that we used in the original experiments
• codes_zcj is the version reproduced by @chujiezheng