# SpellGCN

**Repository Path**: okcd00/spellgcn

## Basic Information

- **Project Name**: SpellGCN
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-12-28
- **Last Updated**: 2021-12-30

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# SpellGCN

[SpellGCN](https://arxiv.org/abs/2004.14166) is a method for chinese spelling check, which embeds the visual and phological knowledge into BERT.
This repository contains data, evaluation and training scripts.

Citation:

```
@inproceedings{DBLP:journals/corr/abs-2004-14166,
  author    = {Xingyi Cheng and
               Weidi Xu and
               Kunlong Chen and
               Shaohua Jiang and
               Feng Wang and
               Taifeng Wang and
               Wei Chu and
               Yuan Qi},
  title={SpellGCN: Incorporating Phonological and Visual Similarities into
               Language Models for Chinese Spelling Check},
  booktitle={ACL},
  year={2020}
}

```
This is the official code for paper titled "SpellGCN: Incorporating Phonological and Visual Similarities into Chinese Spelling Check".

## How to run?

The code is based on Tensorflow==1.13.1 and python 2.7 or higher

Run commands as follows:

```
cd scripts/
conda create -n spellgcn python=2.7.1
source activate spellgcn
pip install tensorflow==1.13.1
sh run.sh
```

Note: Since SpellGCN is based on BERT, the path to the BERT directory should be provided in the run.sh.
The default training data is the combination of data samples from SIGHAN13, SIGHAN14, SIGHAN15.
The additional 270K data samples are absent here due to the lack of permission.

## Contact
fanyin.cxy@alibaba-inc.com and weidi.xwd@alibaba-inc.com