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Auto-Encoder Matching Model

The code for "An Auto-Encoder Matching Model for Learning Utterance-Level Semantic Dependency in Dialogue Generation"

Requirements

  • Python 3
  • Tensorflow >= 1.8
  • mlbootstrap == 0.02

Data Preparation

To use your own data, create a folder data/source/<dataset-name>/ and place the original data in the directory. Then write a parsing script (you can refer to daily.py) and update the config.yaml to include the new data path.

Training

python play.py

Evaluation

Change the last line in play.py to bootstrap.evaluate() and run python play.py

Hyperparameters

You can change the hyperparameters in config.yaml according to your needs.

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The code for "An Auto-Encoder Matching Model for Learning Utterance-Level Semantic Dependency in Dialogue Generation" (EMNLP 2018)

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