PyKoSpacing: Automatic Korean Word Spacing
Introduction
PyKoSpacing is a Python package designed to handle the often tricky issue of automatic word spacing in Korean text. This is crucial for anyone dealing with Korean language processing, as accurate spacing can significantly enhance the quality and accuracy of text analysis. PyKoSpacing shines particularly when handling Korean text from social media or SMS, where spacing is often inconsistent.
Take, for instance, the unspaced sentence "아버지가방에들어가신다." The spacing can drastically change the meaning:
- "아버지가 방에 들어가신다." - "My father enters the room."
- "아버지 가방에 들어가신다." - "My father goes into the bag."
Evidently, proper spacing affects comprehension. To address this, PyKoSpacing employs a deep learning model trained on a large corpus of over 100 million news articles, ensuring reliable and precise word spacing.
Performance
PyKoSpacing boasts impressive accuracies across different test sets, which demonstrate its robust capability in maintaining linguistic integrity:
- Sejong (colloquial style) Corpus: 97.1% accuracy
- OOOO (literary style) Corpus: 94.3% accuracy
Accuracy is measured as the ratio of correctly spaced characters to all characters in the test data, indicating the model's powerful performance.
Installation
PyPI Install
Before installing PyKoSpacing, ensure Python 3 and pip are properly set up on your system. Then, install necessary packages by running:
pip install tensorflow
pip install keras
For specific operating systems like Windows-Ubuntu or Darwin with an M1 chip, additional configurations are required:
- Windows-Ubuntu: Resolve errors with
libstdc++6by installing and upgrading necessary packages. - Darwin (M1): Use Miniforge3 to install TensorFlow specific to Apple's hardware.
You can also install PyKoSpacing directly from GitHub:
pip install git+https://github.com/haven-jeon/PyKoSpacing.git
Example Usage
Below is a basic example illustrating how to use PyKoSpacing to correct word spacing in Korean text:
from pykospacing import Spacing
spacing = Spacing()
print(spacing("김형호영화시장분석가는'1987'의네이버영화정보네티즌10점평에서언급된단어들을지난해12월27일부터올해1월10일까지통계프로그램R과KoNLP패키지로텍스트마이닝하여분석했다."))
This outputs: "김형호 영화시장 분석가는 '1987'의 네이버 영화 정보 네티즌 10점 평에서 언급된 단어들을 지난해 12월 27일부터 올해 1월 10일까지 통계 프로그램 R과 KoNLP 패키지로 텍스트마이닝하여 분석했다."
Advanced Features
PyKoSpacing offers advanced functionalities, such as specifying lists of words that should remain unspaced, setting rules via CSV files, and executing the spacing process via command line.
Handling Mixed Language Input
There are situations where the input may contain English characters alongside Korean text. PyKoSpacing provides parameters ignore and ignore_pattern to manage these scenarios, accommodating for mixed-language text and enhancing spacing accuracy.
Model Architecture
The project's architecture leverages sophisticated deep learning techniques, foundational to achieving the package's high-performance standards. Those interested in training models using more advanced architectures can explore the Train_KoSpacing repository.
Citation
For academic reference, please cite Heewon Jeon's GitHub repository as follows:
@misc{heewon2018,
author = {Heewon Jeon},
title = {KoSpacing: Automatic Korean word spacing},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/haven-jeon/KoSpacing}}
PyKoSpacing serves as a critical tool in the arena of Korean text preprocessing, ensuring text readability and understanding by accurately spacing words automatically. It stands out for its precision, flexibility, and ease of use, making it an invaluable resource for developers and researchers working with Korean text processing.