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https://github.com/optimaize/language-detector

Language Detection Library for Java
https://github.com/optimaize/language-detector

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Language Detection Library for Java

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README 

        
# language-detector



Language Detection Library for Java



    

        com.optimaize.languagedetector

        language-detector

        0.6

    



## Language Support



### 71 Built-in Language Profiles



1. af Afrikaans

1. an Aragonese

1. ar Arabic

1. ast Asturian

1. be Belarusian

1. br Breton

1. ca Catalan

1. bg Bulgarian

1. bn Bengali

1. cs Czech

1. cy Welsh

1. da Danish

1. de German

1. el Greek

1. en English

1. es Spanish

1. et Estonian

1. eu Basque

1. fa Persian

1. fi Finnish

1. fr French

1. ga Irish

1. gl Galician

1. gu Gujarati

1. he Hebrew

1. hi Hindi

1. hr Croatian

1. ht Haitian

1. hu Hungarian

1. id Indonesian

1. is Icelandic

1. it Italian

1. ja Japanese

1. km Khmer

1. kn Kannada

1. ko Korean

1. lt Lithuanian

1. lv Latvian

1. mk Macedonian

1. ml Malayalam

1. mr Marathi

1. ms Malay

1. mt Maltese

1. ne Nepali

1. nl Dutch

1. no Norwegian

1. oc Occitan

1. pa Punjabi

1. pl Polish

1. pt Portuguese

1. ro Romanian

1. ru Russian

1. sk Slovak

1. sl Slovene

1. so Somali

1. sq Albanian

1. sr Serbian

1. sv Swedish

1. sw Swahili

1. ta Tamil

1. te Telugu

1. th Thai

1. tl Tagalog

1. tr Turkish

1. uk Ukrainian

1. ur Urdu

1. vi Vietnamese

1. wa Walloon

1. yi Yiddish

1. zh-cn Simplified Chinese

1. zh-tw Traditional Chinese



User danielnaber has made available a profile for Esperanto on his website, see open tasks.



There are two kinds of profiles. The standard ones created from Wikipedia articles and similar.

And the "short text" profiles created from Twitter tweets. Fewer language profiles exist for the

short text, more would be available, see https://github.com/optimaize/language-detector/issues/57



### Other Languages



You can create a language profile for your own language easily.

See https://github.com/optimaize/language-detector/blob/master/src/main/resources/README.md



## How it Works



The software uses language profiles which were created based on common text for each language.

N-grams http://en.wikipedia.org/wiki/N-gram were then extracted from that text, and that's what is stored in the profiles.



When trying to figure out in what language a certain text is written, the program goes through the same process:

It creates the same kind of n-grams of the input text. Then it compares the relative frequency of them, and finds the

language that matches best.



### Challenges



This software does not work as well when the input text to analyze is short, or unclean. For example tweets.



When a text is written in multiple languages, the default algorithm of this software is not appropriate.

You can try to split the text (by sentence or paragraph) and detect the individual parts. Running the language guesser

on the whole text will just tell you the language that is most dominant, in the best case.



This software cannot handle it well when the input text is in none of the expected (and supported) languages.

For example if you only load the language profiles from English and German, but the text is written in French,

the program may pick the more likely one, or say it doesn't know. (An improvement would be to clearly detect that

it's unlikely one of the supported languages.)



If you are looking for a language detector / language guesser library in Java, this seems to be the best open source

library you can get at this time. If it doesn't need to be Java, you may want to take a look at https://code.google.com/p/cld2/



## How to Use



#### Language Detection for your Text



    //load all languages:

    List languageProfiles = new LanguageProfileReader().readAllBuiltIn();



    //build language detector:

    LanguageDetector languageDetector = LanguageDetectorBuilder.create(NgramExtractors.standard())

            .withProfiles(languageProfiles)

            .build();



    //create a text object factory

    TextObjectFactory textObjectFactory = CommonTextObjectFactories.forDetectingOnLargeText();



    //query:

    TextObject textObject = textObjectFactory.forText("my text");

    Optional lang = languageDetector.detect(textObject);



#### Creating Language Profiles for your Training Text



See https://github.com/optimaize/language-detector/wiki/Creating-Language-Profiles



## How You Can Help



If your language is not supported yet, then you can provide clean "training text", that is, common text written in your

language. The text should be fairly long (a couple of pages at the very least). If you can provide that, please open

a ticket.



If your language is supported already, but not identified clearly all the time, you can still provide such training

text. We might then be able to improve detection for your language.



If you're a programmer, dig in the source and see what you can improve. Check the open tasks.



## Memory Consumption



Loading all 71 language profiles uses 74MB ram to store the data in memory.

For memory considerations see https://github.com/optimaize/language-detector/wiki/Memory-Consumption



## History and Changes



This project is a fork of a fork, the original author is Nakatani Shuyo.

For detail see https://github.com/optimaize/language-detector/wiki/History-and-Changes



## Where it's used



An adapted version of this is used by the http://www.NameAPI.org server.



https://www.languagetool.org/ is a proof-reading software for LibreOffice/OpenOffice, for the Desktop and for Firefox.



## License



Apache 2 (business friendly)



## Authors



Nakatani Shuyo, Fabian Kessler, Francois ROLAND, Robert Theis



For detail see https://github.com/optimaize/language-detector/wiki/Authors



## For Maven Users



The project is in Maven central http://search.maven.org/#artifactdetails%7Ccom.optimaize.languagedetector%7Clanguage-detector%7C0.4%7Cjar this is the latest version:



    

        com.optimaize.languagedetector

        language-detector

        0.6