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[Utility & Helpers](/categories/utility) 4. / 5. andywer/language-detector ActiveLibrary[Utility & Helpers](/categories/utility) andywer/language-detector ========================= PHP library to detect the language of any free text. 0.2.0(10y ago)026BSD-4-ClausePHP Since Apr 11Pushed 10y ago1 watchersCompare [ Source](https://github.com/andywer/language-detector)[ Packagist](https://packagist.org/packages/andywer/language-detector)[ RSS](/packages/andywer-language-detector/feed)WikiDiscussions master Synced 1mo ago READMEChangelogDependencies (2)Versions (8)Used By (0) LanguageDetector [![Build Status](https://camo.githubusercontent.com/bd47fc04624b1f430283bc11f7c77436b5b89abcee0b53cf8cfdc53784008b2c/68747470733a2f2f7472617669732d63692e6f72672f616e64797765722f6c616e67756167652d6465746563746f722e706e67)](https://travis-ci.org/andywer/language-detector) =============================================================================================================================================================================================================================================================================================== [](#languagedetector-) PHP library to detect languages from any free text. It follows the approach described in the [paper](http://scholar.google.com.py/scholar?q=N-Gram-Based+Text+Categorization), a given text is tokenized into [N-Grams](http://en.wikipedia.org/wiki/N-gram) (we cleanup whitespaces before doing this step). Then we sort the `tokens` and we compare against a language `model`. *Fork of [crodas/languagedetector](https://github.com/crodas/LanguageDetector), since the original package seems abandoned.* How it works ------------ [](#how-it-works) The first thing we need is a `language model` (which looks like [this file](https://github.com/crodas/LanguageDetector/blob/master/example/datafile.php)) that is used to compare the texts against at classification time. This process must done *before* anything, and it can be generated with an script similar to [this file](https://github.com/crodas/LanguageDetector/blob/master/example/learn.php). ``` // register the autoloader require 'lib/LanguageDetector/autoload.php'; // it could use a little bit of memory, but it's fine // because this process runs once. ini_set('memory_limit', '1G'); // we load the configuration (which will be serialized // later into our language model file $config = new LanguageDetector\Config; $c = new LanguageDetector\Learn($config); foreach (glob(__DIR__ . '/samples/*') as $file) { // feed with examples ('language', 'text'); $c->addSample(basename($file), file_get_contents($file)); } // some callback so we know where the process is $c->addStepCallback(function($lang, $status) { echo "Learning {$lang}: $status\n"; }); // save it in `datafile`. // we currently support the `php` serialization but it's trivial // to add other formats, just extend `\LanguageDetector\Format\AbstractFormat`. //You can check example at https://github.com/crodas/LanguageDetector/blob/master/lib/LanguageDetector/Format/PHP.php $c->save(AbstractFormat::initFormatByPath('language.php')); ``` Once we have our language model file (in this case `language.php`) we're ready to classify texts by their language. ``` // register the autoloader require 'lib/LanguageDetector/autoload.php'; // we load the language model, it would create // the $config object for us. $detect = LanguageDetector\Detect::initByPath('language.php'); $lang = $detect->detect("Agricultura (-ae, f.), sensu latissimo, est summa omnium artium et scientiarum et technologiarum quae de terris colendis et animalibus creandis curant, ut poma, frumenta, charas, carnes, textilia, et aliae res e terra bene producantur. Specialius, agronomia est ars et scientia quae terris colendis student, agricultio autem animalibus creandis.") var_dump($lang); ``` And that's it. Algorithms ---------- [](#algorithms) The project is designed to work with modules, which means you can provide your own algorithm for `sorting` and `comparing` the N-Grams. By default the library implements the [PageRank](http://en.wikipedia.org/wiki/PageRank) as `sorting` algorithm, and *out of place* (described in the paper) as `comparing`. In order to supply your own algorithms, you must change the `$config` at *learning stage* to load your own classes (which by the way should implement some interaces). Language Detection Training Files --------------------------------- [](#language-detection-training-files) Have a look at `example/samples` directory. For more advanced traning data, visit the [Leipzig Corpora Download Page](http://corpora2.informatik.uni-leipzig.de/download.html). Languages with non-latin characters ----------------------------------- [](#languages-with-non-latin-characters) Remember to set the Config's `mb` property (already before creating the language model) if you train for languages based on non-latin characters. Use UTF-8 encoded texts. ### Health Score 26 — LowBetter than 43% of packages Maintenance20 Infrequent updates — may be unmaintained Popularity6 Limited adoption so far Community13 Small or concentrated contributor base Maturity58 Maturing project, gaining track record Bus Factor1 Top contributor holds 77% of commits — single point of failure How is this calculated?**Maintenance (25%)** — Last commit recency, latest release date, and issue-to-star ratio. Uses a 2-year decay window. **Popularity (30%)** — Total and monthly downloads, GitHub stars, and forks. Logarithmic scaling prevents top-heavy scores. **Community (15%)** — Contributors, dependents, forks, watchers, and maintainers. Measures real ecosystem engagement. **Maturity (30%)** — Project age, version count, PHP version support, and release stability. ### Release Activity Cadence Every ~346 days Total 3 Last Release 3884d ago ### Community Maintainers ![](https://www.gravatar.com/avatar/8ff954113ccc159a8aeafc8805da9dd73e33f6a85bbfd5c3e9117481c3b0f08d?d=identicon)[andywer](/maintainers/andywer) --- Top Contributors [![crodas](https://avatars.githubusercontent.com/u/36463?v=4)](https://github.com/crodas "crodas (47 commits)")[![mente](https://avatars.githubusercontent.com/u/391997?v=4)](https://github.com/mente "mente (7 commits)")[![andywer](https://avatars.githubusercontent.com/u/1842462?v=4)](https://github.com/andywer "andywer (3 commits)")[![adam-lynch](https://avatars.githubusercontent.com/u/1427241?v=4)](https://github.com/adam-lynch "adam-lynch (2 commits)")[![pborreli](https://avatars.githubusercontent.com/u/77759?v=4)](https://github.com/pborreli "pborreli (1 commits)")[![sasezaki](https://avatars.githubusercontent.com/u/42755?v=4)](https://github.com/sasezaki "sasezaki (1 commits)") ### Embed Badge ![Health badge](/badges/andywer-language-detector/health.svg) ``` [![Health](https://phpackages.com/badges/andywer-language-detector/health.svg)](https://phpackages.com/packages/andywer-language-detector) ``` PHPackages © 2026 [Directory](/)[Categories](/categories)[Trending](/trending)[Changelog](/changelog)[Analyze](/analyze)