LanguageTool

LanguageTool is a free and open-source grammar, style, and spell checker, and all its features are available for download.[4] The LanguageTool website connects to a proprietary sister project called LanguageTool Premium (formerly LanguageTool Plus), which provides improved error detection for English and German, as well as easier revision of longer texts, following the open-core model.

LanguageTool
Developer(s)Daniel Naber and Marcin Miłkowski
Initial release15 August 2005; 18 years ago (2005-08-15)
Stable release
6.4[1] Edit this on Wikidata / 28 March 2024
Repository
Written inJava
PlatformJava SE
Size
  • Desktop app: 156 MB[2]
  • n-gram data: 8.34 GB[3]
TypeGrammar checker
LicenseGNU LGPL v2.1+
Websitelanguagetool.org Edit this on Wikidata

Overview

LanguageTool was started by Daniel Naber for his diploma thesis[5] in 2003 (then written in Python). It now supports 31 languages, each developed by volunteer maintainers, usually native speakers of each language.[6] Based on error detection patterns, rules are created and then tested for a given text.The core app itself is free and open-source and can be downloaded for offline use. Some languages use 'n-gram' data,[7] which is massive and requires considerable processing power and I/O speed, for some extra detections. As such, LanguageTool is also offered as a web service that does the processing of 'n-grams' data on the server-side. LanguageTool Premium also uses n-grams as part of its freemium business model.

LanguageTool web service can be used via a web interface in a web browser, or via a specialized client-side plug-ins for Microsoft Office, LibreOffice, Apache OpenOffice, Vim, Emacs, Firefox, Thunderbird, and Google Chrome.

LanguageTool does not check a sentence for grammatical correctness, but whether it contains typical errors. Therefore, it is easy to invent ungrammatical sentences that LanguageTool will still accept. Error detection succeeds with a variety of rules based on XML or written in Java.[8] XML-based rules can be created using an online form.[9]

More recent developments rely on large n-gram libraries that offer suggestions for improving misspellings with the help of artificial neural networks.[10]

See also

References