Language Identification with Facebook FastText

This is a small JavaScript library for use in Node.js environments, providing the possibility to identify the language of a piece of text with the help of the Wikipedia/Tatoeba/SETimes-derived pre-trained LID-176 model and the fast and efficient Facebook FastText Machine-Learning-based text classification engine. The classification result is a list of identified languages (identified by their two-character ISO codes) and their classification probability.

The LID-176 model is licensed under CC-BY-SA and not part of this module. It is 126 MB in size and detects 176 languages. It is automatically downloaded from its external origin on npm install. Applications using this Node.js module have to take the license of this external model into account. The module cld (Apache licensed, 160 languages) and the module franc (MIT licensed, 188 or 400 languages) are decent alternatives.

$ npm install fasttext-lid

(async () => {
    const LID = require("fasttext-lid")
    const lid = new LID()

    console.log(await lid.predict("FastText-LID provides a great language identification"))
    console.log(await lid.predict("FastText-LID bietet eine hervorragende Sprachidentifikation"))
    console.log(await lid.predict("FastText-LID fornisce un ottimo linguaggio di identificazione"))
    console.log(await lid.predict("FastText-LID fournit une excellente identification de la langue"))
    console.log(await lid.predict("FastText-LID proporciona una gran identificación de idioma"))
    console.log(await lid.predict("FastText-LID обеспечивает отличную идентификацию языка"))
    console.log(await lid.predict("FastText-LID提供了很好的語言識別"))
})()

Output:

[ { lang: 'en', prob: 0.6313226222991943 } ]
[ { lang: 'de', prob: 0.9137916564941406 } ]
[ { lang: 'it', prob: 0.974501371383667 } ]
[ { lang: 'fr', prob: 0.7358829975128174 } ]
[ { lang: 'es', prob: 0.9211937189102173 } ]
[ { lang: 'ru', prob: 0.9899846911430359 } ]
[ { lang: 'zh', prob: 0.8515647649765015 } ]

• new LID({ model?: string }): LID:
  Instantiate a new Language Identification object. Optionally, you could pass it the path to a different FastText model. The default is to use the LID-176 model which was downloaded on npm install.

• LID::predict(text: string, k?: number }): [ { lang: string, prob: number }* ]:
  Predict the language for text and return the first k predictions (in decreasing probability order). The default is 1 for k.

Copyright © 2018-2023 Dr. Ralf S. Engelschall (http://engelschall.com/)

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

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