Deepcut

A Thai word tokenization library using Deep Neural Network.

Performance

The Convolutional Neural network is trained from 90% of NECTEC's BEST corpus(consists of 4 sections, article, news, novel and wikipedia) and test on the rest 10%. It is a binary classification model trying to predict whether a character is the beginning of word or not. The results calculated from only 'true' class are as follow

f1 score: 98.8%
precision score: 98.6%
recall score: 99.1%

Installation

On terminal, just type

  pip install deepcut

Make sure you are using tensorflow backend in keras by making sure ~/.keras/keras.json is as follows (see also https://keras.io/backend/)

  {
    "floatx": "float32",
    "epsilon": 1e-07,
    "backend": "tensorflow",
    "image_data_format": "channels_last"
  }

Usage

import deepcut
deepcut.tokenize('ตัดคำได้ดีมาก')

output will be in list format

['ตัด','คำ','ได้','ดี','มาก']

Notes

Some texts might not be segmented as we would expected (e.g. 'โรงเรียน' -> ['โรง', 'เรียน']), this is because of

BEST corpus (training data) tokenizes word this way
They are unseen/new words -> Ideally, this would be cured by having better corpus but it's not very practical so I am thinking of doing semi supervised learning to incorporate new examples.

Any suggestion and comment are welcome, please post it in issue section.

Contributors

Rakpong Kittinaradorn
Korakot Chaovavanich