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Language detection for news powered by fasttext

Project description

fastlangid

Language identification including traditional and simplified chinese.

Why? and Who is this package for

This is a langugage identification language focus in providing higher accuracy in Japanese, Korean, and Chinese language compare to the original fasttext model ( lid.176.ftz ). This package also include identification for simplified and traditional chinese language.

We are able to achieve higher accuracy by including an additional language identification model to handle low confidence score for Japanese, Korean, Chinese.

The training data for the supplement model was drawn from Common Crawl Corpus and Currents API internal language dataset.

We wish to support cantonese language in the upcoming future. Feel free to contact us if you would like to provide related corpus.

For more details see fasttext_issues.py

Install

$ pip install fastlangid

Supported Languages

Supports 177 languages. The ISO codes for the corresponding languages are as below.

af als am an ar arz as ast av az azb ba bar bcl be bg bh bn bo bpy br bs bxr ca cbk
ce ceb ckb co cs cv cy da de diq dsb dty dv el eml en eo es et eu fa fi fr frr fy ga
gd gl gn gom gu gv he hi hif hr hsb ht hu hy ia id ie ilo io is it ja jbo jv ka kk km
kn ko krc ku kv kw ky la lb lez li lmo lo lrc lt lv mai mg mhr min mk ml mn mr mrj ms
mt mwl my myv mzn nah nap nds ne new nl nn no oc or os pa pam pfl pl pms pnb ps pt qu
rm ro ru rue sa sah sc scn sco sd sh si sk sl so sq sr su sv sw ta te tg th tk tl tr
tt tyv ug uk ur uz vec vep vi vls vo wa war wuu xal xmf yi yo yue zh-hans zh-hant

Reference

Enriching Word Vectors with Subword Information

[1] P. Bojanowski*, E. Grave*, A. Joulin, T. Mikolov, Enriching Word Vectors with Subword Information

@article{bojanowski2016enriching,
  title={Enriching Word Vectors with Subword Information},
  author={Bojanowski, Piotr and Grave, Edouard and Joulin, Armand and Mikolov, Tomas},
  journal={arXiv preprint arXiv:1607.04606},
  year={2016}
}

Bag of Tricks for Efficient Text Classification

[2] A. Joulin, E. Grave, P. Bojanowski, T. Mikolov, Bag of Tricks for Efficient Text Classification

@article{joulin2016bag,
  title={Bag of Tricks for Efficient Text Classification},
  author={Joulin, Armand and Grave, Edouard and Bojanowski, Piotr and Mikolov, Tomas},
  journal={arXiv preprint arXiv:1607.01759},
  year={2016}
}

FastText.zip: Compressing text classification models

[3] A. Joulin, E. Grave, P. Bojanowski, M. Douze, H. Jégou, T. Mikolov, FastText.zip: Compressing text classification models

@article{joulin2016fasttext,
  title={FastText.zip: Compressing text classification models},
  author={Joulin, Armand and Grave, Edouard and Bojanowski, Piotr and Douze, Matthijs and J{\'e}gou, H{\'e}rve and Mikolov, Tomas},
  journal={arXiv preprint arXiv:1612.03651},
  year={2016}
}

Project details


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