Implement korean restaurant reservation dialogue system based on hybrid code network(https://github.com/johndpope/hcn).
Add post processing and edit templates to adjust korean dataset which we created. 759 training dialogue data and 190 test dialogue data were used for Korean restaurant reservation dialogue system model.
Experimental results show that the proposed system has 95% accuracy of per-response and 63% accuracy of per-dialogue.

1. cd data/
2. Downalod word2vec
3. tar -xvf korean_word2vec.tar.gz

python3 train.py

The Korean dataset is consist of 1000 dialogues.(data/korean_train)

• Per-response Accuracy : 95%
  
• Per-dialogue Accuracy : 71%