Schema-guided User Satisfaction Modeling for Task-oriented Dialogues

This repository contains the code for the paper titled Schema-guided User Satisfaction Modeling for Task-oriented Dialogues, which is accepted by the ACL 2023.

1. Installation

conda create --name usm python=3.8
conda install pytorch torchvision torchaudio pytorch-cuda=11.7 -c pytorch -c nvidia
pip install -r requirements.txt

2. Preprocess the data

The dataset can be downloaded via the following repository: USDA.

3. Training

./train.sh

4. Testing

./test.sh

Bugs or questions?

If you have any inquiries pertaining to the code or the paper, please do not hesitate to contact Yue Feng. In case you encounter any issues while utilising the code or wish to report a bug, you may open an issue. We kindly request that you provide specific details regarding the problem so that we can offer prompt and efficient assistance.

Citation

@inproceedings{yue2023usm,
  title={Schema-guided User Satisfaction Modeling for Task-oriented Dialogues},
  author={Yue Feng, Yunlong Jiao, Animesh Prasad, Nikolaos Aletras, Emine Yilmaz and Gabriella Kazai},
  year={2023},
  address = {Toronto, Canada},
  booktitle = {The 61st Annual Meeting of the Association for Computational Linguistics: ACL 2023},
  publisher = {Association for Computational Linguistics},
}

Authors

• Yue Feng: Main contributor

Security

See CONTRIBUTING for more information.

License

This project is licensed under the Apache-2.0 License.