Babel Street Analytics API

 https://analytics.babelstreet.com/rest/v1/language

https://raw.githubusercontent.com/rosette-api/curl-examples/develop/examples/language.curl

Language Identifier identifies the language or languages of the input text. The endpoint returns a list of languages identified in descending order of confidence, so the first result is the best. Language Identifier can also detect different language regions in a multilingual document. When multilingual is set to true, it returns a list of language regions in addition to the whole-document results.

The input data may be in any of 364 language–encoding–script combinations, involving 56 languages, 48 encodings, and 18 writing scripts. The language identifier uses an n-gram algorithm to detect language. Each of the 155 built-in profiles contains the quad-grams (i.e., four consecutive bytes) that are most frequently encountered in documents in a given language, encoding, and script. The default number of n-grams is 10,000 for double-byte encodings and 5,000 for single-byte encodings.

When input text is submitted for detection, a similar n-gram profile is built based on that data. The input profile is then compared with all the built-in profiles (a vector distance measure between the input profile and the built-in profile is calculated). The pre-built profiles are then returned in ascending order by the (shortest) distance of the input from the pre-built profiles.

For all supported languages, the endpoint provides a different proprietary algorithm for detecting the language of short strings (140 characters or less).

{
  "content": "string",
  "options": {
    "koreanDialects": false,
    "multilingual": false
  }
}

{
  "languageDetections": [
    {
      "language": "string",
      "confidence": number
    }
  ]
}

{
  "supportedLanguages": [
    {
      "language": "string",
      "script": "string",
      "licensed": boolean
    }
  ]
}