hjpwhu / ancient-chinese-poem-generator

course project

Ancient-Chinese-Poem-Generator

This generator generates Chinese poem automatically when given the first sentence or the initial characters. Basically, it's a rule based sequence to character model. 2 or 3 LSTMs are stacked together and trained as a generative model. To make poem more human-written alike, tone pattern rule is also added.

This is a group project for CSCI 544, Applied Natural Language Processing.

Members:

• Shengyu Chen
• Shuai Zhou
• Yizhao He
• Zichen Yang

Live Demo

We provide a User Interface to demo our Poem Generator: http://poem.knotesapp.com/

For fast testing, type in the first sentence: 春至花海棠 , leave intial characters empty and press Generate button

Requirements

• python 3
• numpy, scipy
• yaml
• HDF5 and h5py
• TensorFlow
• Keras

Usage

Train

python ./lstm/train.py [-m SAVE_PATH] [-d DATA_PATH] [-v]

Generate

python ./lstm/generate.py [-p PRIME] [-s SENTENCE] [-v VOCAB_PATH] [-w MODEL_WEIGHTS_PATH] [-m MODEL_STRUCT_PATH]

Sample

春至花海棠，
衰家夜有人，
一去见家悲，
今气又去禅。

Parameters

The first version is a sequence to word language model based on LSTM programmed in Python with Keras.

All poems used in training are 5-character simplified Chinese poems written in Tang dynasty.

• data size: 16,000+ poems
• memory units number: 256 to 700
• dropout: 0.2
• batch size: 64 to 256
• epoch: 100+
• sequence length: 6 or 8
• number of LSTM layers: 2 to 3

Data Source

All poetry data comes from JackyGao's work, which is a great contribution for this model. Peotries are labed with tone patterns which are the rules Chinese poems need to follow.

License

MIT