gaybro8777 / amm

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

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

• Get the DailyDialog dataset at http://yanran.li/dailydialog.html
• Unzip the downloaded file
• Move dialogues_text.txt to data/source/daily/dialogues_text.txt

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.