Codebase for Unsupervised Dialog Structure Learning, published as a long paper in NAACL 2019. The codebase is developed based on NeuralDialog-CVAE.
If you use the datasets or any source codes included in this repository in your work, please cite the following paper. The bibtex is listed below:
@article{shi2019unsupervised,
title={Unsupervised Dialog Structure Learning},
author={Shi, Weiyan and Zhao, Tiancheng and Yu, Zhou},
journal={arXiv preprint arXiv:1904.03736},
year={2019}
}
https://github.com/Liang-Qiu/SVRNN-dialogues
Listed in the requirements.txt. I was using a pretty old tensorflow version when first developing the project. I think most of the major functions are still supported but haven't tested it on the new versions yet.
python 2
tensorflow == 1.0.1
python main.py --result_path data/results/whatever_name.pkl
python main.py --result_path data/results/whatever_name.pkl --forward_only True --test_path runSomeTimeStamp
After the training, there will be a directory at working/runSomeTimeStamp (e.g. run1532935232), just copy the dir name and pass it to test_path.
In interpretation.py.