[[language-intro]] == Getting Started with Languages Elasticsearch ships with a collection of language analyzers that provide good, basic, out-of-the-box ((("language analyzers")))((("languages", "getting started with")))support for many of the world's most common languages: Arabic, Armenian, Basque, Brazilian, Bulgarian, Catalan, Chinese, Czech, Danish, Dutch, English, Finnish, French, Galician, German, Greek, Hindi, Hungarian, Indonesian, Irish, Italian, Japanese, Korean, Kurdish, Norwegian, Persian, Portuguese, Romanian, Russian, Spanish, Swedish, Turkish, and Thai. These analyzers typically((("language analyzers", "roles performed by"))) perform four roles: * Tokenize text into individual words: + `The quick brown foxes` -> [`The`, `quick`, `brown`, `foxes`] * Lowercase tokens: + `The` -> `the` * Remove common _stopwords_: + [`The`, `quick`, `brown`, `foxes`] -> [`quick`, `brown`, `foxes`] * Stem tokens to their root form: + `foxes` -> `fox` Each analyzer may also apply other transformations specific to its language in order to make words from that((("language analyzers", "other transformations specific to the language"))) language more searchable: * The `english` analyzer ((("english analyzer")))removes the possessive `'s`: + `John's` -> `john` * The `french` analyzer ((("french analyzer")))removes _elisions_ like `l'` and `qu'` and _diacritics_ like `¨` or `^`: + `l'église` -> `eglis` * The `german` analyzer normalizes((("german analyzer"))) terms, replacing `?` and `ae` with `a`, or `?` with `ss`, among others: + `?u?erst` -> `ausserst`