fengfly2014 / deeputteranceaggregation Goto Github PK

Code and sample data accompanying the paper Modeling Multi-turn Conversation with Deep Utterance Aggregation.

We release E-commerce Dialogue Corpus, comprising a training data set, a development set and a test set for retrieval based chatbot. The statistics of E-commerical Conversation Corpus are shown in the following table.

The full corpus can be downloaded from https://drive.google.com/file/d/154J-neBo20ABtSmJDvm7DK0eTuieAuvw/view?usp=sharing.

label \t conversation utterances (splited by \t) \t response

We also release our source code to help others reproduce our result

Our code is compatible with python2 so for all commands listed below python is python2

We strongly suggest you to use conda to control the virtual environment

• Install requirement

  pip install -r requirements.txt

• Pretrain word embedding

  python train_word2vec.py ./ECD_sample/train embedding

• Preprocess the data

  python PreProcess.py --train_dataset ./ECD_sample/train --valid_dataset ./ECD_sample/valid --test_dataset ./ECD_sample/test --pretrained_embedding embedding --save_dataset ./ECD_sample/all

• Train the model

  bash train.sh

If you encounter some cuda issues, please check your environment. For reference,

Theano 0.9.0
Cuda 8.0
Cudnn 5.1

If you use this code please cite our paper:

@inproceedings{zhang2018dua,
    title = {Modeling Multi-turn Conversation with Deep Utterance Aggregation},
    author = {Zhang, Zhuosheng and Li, Jiangtong and Zhu, Pengfei and Zhao, Hai},
    booktitle = {Proceedings of the 27th International Conference on Computational Linguistics (COLING 2018)},
    pages={3740--3752},
    year = {2018}
}