Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/XingxingZhang/rnnpg
Code for Chinese Poetry Generation with Recurrent Neural Networks (EMNLP 2014)
https://github.com/XingxingZhang/rnnpg
Last synced: 13 days ago
JSON representation
Code for Chinese Poetry Generation with Recurrent Neural Networks (EMNLP 2014)
- Host: GitHub
- URL: https://github.com/XingxingZhang/rnnpg
- Owner: XingxingZhang
- Created: 2015-08-24T11:45:52.000Z (about 9 years ago)
- Default Branch: master
- Last Pushed: 2016-11-13T19:30:11.000Z (almost 8 years ago)
- Last Synced: 2024-08-01T16:17:43.195Z (3 months ago)
- Language: C++
- Homepage:
- Size: 199 KB
- Stars: 161
- Watchers: 11
- Forks: 48
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Chinese Poetry Generation with Recurrent Neural Networks
This project includes the code/model for the paper
[Chinese Poetry Generation with Recurrent Neural Networks](http://aclweb.org/anthology/D/D14/D14-1074.pdf)
```
@InProceedings{zhang-lapata:2014:EMNLP2014,
author = {Zhang, Xingxing and Lapata, Mirella},
title = {Chinese Poetry Generation with Recurrent Neural Networks},
booktitle = {Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
month = {October},
year = {2014},
address = {Doha, Qatar},
publisher = {Association for Computational Linguistics},
pages = {670--680},
url = {http://www.aclweb.org/anthology/D14-1074}
}
```
# Acknowledgement
Our implementation is greatly inspired by Tomas Mikolov's [rnnlm toolkit](http://rnnlm.org/).
We would like to thank Tomas Mikolov for making his code public available.
# Dataset
Download the complete dataset from [here](http://homepages.inf.ed.ac.uk/mlap/Data/EMNLP14/)
# Dependencies
* [KenLM](https://kheafield.com/code/kenlm/)
* G++ (4.4.7)
* Java (1.8.0_51, 1.6 or 1.7 should also be fine)
* Python (2.7)
# Installation
1) Install [KenLM](https://kheafield.com/code/kenlm/). Also remember to add kenlm to your LD_LIBRARY_PATH
```
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/afs/inf.ed.ac.uk/user/s12/s1270921/usr/kenlm/lib
```
2) Go to *rnnpg* folder and modify the Makefile (see below). Direct `INCLUDES` and `LDFLAGS` to your KenLM library. Also modify the Makefiles in *rnnpg-decoder* and *rnnpg-generator*.
3) Make everything by ./INSTALL.sh
```
OUT_EXEC = rnnpg
OBJS = $(patsubst %.cpp, %.o, $(wildcard *.cpp))
CC = g++
CPPFLAGS = -O3 -funroll-loops -ffast-math -finline-functions -Wall -Winline -pipe -DKENLM_MAX_ORDER=6
INCLUDES = -I/afs/inf.ed.ac.uk/user/s12/s1270921/usr/kenlm
LDFLAGS = -L/afs/inf.ed.ac.uk/user/s12/s1270921/usr/kenlm/lib -lkenlm
all : $(OUT_EXEC)
rm *.o
$(OUT_EXEC) : $(OBJS)
$(CC) -o $@ $^ $(INCLUDES) $(LDFLAGS)
%.o : %.cpp
$(CC) $(CPPFLAGS) -c $< -o $@ $(INCLUDES)
clean:
rm -f *.o
rm -f $(OUT_EXEC)
```
# Run Experiments
Download data/model from [here](https://drive.google.com/file/d/0B6-YKFW-MnbOYnJDeWVXRnlObzA/view?usp=sharing)
```
# move MISC.tar.bz2 to the root folder of this project, then
tar jxvf MISC.tar.bz2
```
**1. Perplexity**
```
cd experiments
./ppl.sh
```
**2. Generation**
```
cd experiments
./generation.sh
```
Enjoy the generated poems!
**3. BLEU**
Download from [here](https://drive.google.com/file/d/0B6-YKFW-MnbORk16WmNXbDhsVk0/view?usp=sharing)
```
tar jxvf BLEU2-final.tar.bz2
cd BLEU2-final
cd MERT_channel-1_RNN-CB-POS-LM-Eval-BLEU2
python showBLEU.py .
```