xiximeng / ecm Goto Github PK

This project is a tensorflow implement of our work, ECM.

Due to the copyright of the STC dataset, you can ask Lifeng Shang ([email protected]) for the STC dataset (Neural Responding Machine for Short-Text Conversation), and build the ESTC dataset follow the instruction in the Data Preparation Section of our paper, ECM.

For your convenience, we also recommand you implement your model using the nlpcc2017 dataset (http://aihuang.org:8000/p/challenge.html), which has more than 1 million Weibo post-response pairs with emotional labels.

1. train

python baseline.py --use_emb --use_imemory --use_ememory

You can remove "--use_emb", "--use_imemory", "--use_ememory" to remove the embedding, internal memory, and external memory module respectively.

2. test

python baseline.py --use_emb --use_imemory --use_ememory --decode

You can test and apply the ecm model using this command. Note: the input words should be splitted by ' ', for example, '我 很 喜欢 你 ！', or you can add the chinese text segmentation module in split() function.

• Python 2.7
• Tensorflow 0.12
• Numpy