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ESIM for Multi-turn Response Selection Task

Home Page: https://arxiv.org/pdf/1901.02609.pdf

License: Apache License 2.0

Python 98.53% Shell 1.47%

esim-response-selection's Introduction

ESIM for Multi-turn Response Selection Task

Introduction

If you use this code as part of any published research, please acknowledge one of the following papers.

@inproceedings{chen2019sequential,
  title={Sequential Matching Model for End-to-end Multi-turn Response Selection},
  author={Chen, Qian and Wang, Wen},
  booktitle={ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={7350--7354},
  year={2019},
  organization={IEEE}
}
@article{DBLP:journals/corr/abs-1901-02609,
  author    = {Chen, Qian and Wang, Wen},
  title     = {Sequential Attention-based Network for Noetic End-to-End Response Selection},
  journal   = {CoRR},
  volume    = {abs/1901.02609},
  year      = {2019},
  url       = {http://arxiv.org/abs/1901.02609},
}

Requirement

  1. gensim
pip install gensim
  1. Tensorflow 1.9-1.12 + Python2.7

Steps

  1. Download the Ubuntu dataset released by (Xu et al, 2017)

  2. Unzip the dataset and put data directory into data/

  3. Preprocess dataset, including concatenatate context and build vocabulary

cd data
python prepare.py
  1. Train word2vec
bash run_train_word2vec.sh
  1. Train and test ESIM, the log information is in log.txt file. You could find an example log file in log_example.txt.
cd scripts/esim
bash run.sh

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