Go to console

Identify the language of text with ML Kit on Android

You can use ML Kit to identify the language of a string of text. You can get the string's most likely language or get confidence scores for all of the string's possible languages.

ML Kit recognizes text in 103 different languages in their native scripts. In addition, romanized text can be recognized for Arabic, Bulgarian, Chinese, Greek, Hindi, Japanese, and Russian.

See the ML Kit quickstart sample on GitHub for an example of this API in use.

Before you begin

  1. If you haven't already, add Firebase to your Android project.
  2. In your project-level build.gradle file, make sure to include Google's Maven repository in both your buildscript and allprojects sections.
  3. Add the dependencies for the ML Kit Android libraries to your module (app-level) Gradle file (usually app/build.gradle):
    dependencies {
      // ...
    
      implementation 'com.google.firebase:firebase-ml-natural-language:21.0.2'
      implementation 'com.google.firebase:firebase-ml-natural-language-language-id-model:20.0.5'
    }
    apply plugin: 'com.google.gms.google-services'
    

Identify the language of a string

To identify the language of a string, get an instance of FirebaseLanguageIdentification, and then pass the string to the identifyLanguage() method.

For example:

FirebaseLanguageIdentification languageIdentifier =
        FirebaseNaturalLanguage.getInstance().getLanguageIdentification();
languageIdentifier.identifyLanguage(text)
      .addOnSuccessListener(
          new OnSuccessListener<String>() {
            @Override
            public void onSuccess(@Nullable String languageCode) {
              if (languageCode != "und") {
                Log.i(TAG, "Language: " + languageCode);
              } else {
                Log.i(TAG, "Can't identify language.");
              }
            }
          })
      .addOnFailureListener(
          new OnFailureListener() {
            @Override
            public void onFailure(@NonNull Exception e) {
              // Model couldn’t be loaded or other internal error.
              // ...
            }
          });

If the call succeeds, a BCP-47 language code is passed to the success listener, indicating the language of the text. See the complete list of supported languages. If no language could be confidently detected, the code und (undetermined) is passed.

By default, ML Kit returns a value other than und only when it identifies the language with a confidence value of at least 0.5. You can change this threshold by passing a FirebaseLanguageIdentificationOptions object to getLanguageIdentification():

FirebaseLanguageIdentification languageIdentifier = FirebaseNaturalLanguage
        .getInstance()
        .getLanguageIdentification(
                new FirebaseLanguageIdentificationOptions.Builder()
                        .setIdentifyLanguageConfidenceThreshold(0.34f)
                        .build());

Get the possible languages of a string

To get the confidence values of a string's most likely languages, get an instance of FirebaseLanguageIdentification, and then pass the string to the identifyAllLanguages() method.

For example:

FirebaseLanguageIdentification languageIdentifier =
        FirebaseNaturalLanguage.getInstance().getLanguageIdentification();
languageIdentifier.identifyAllLanguages(text)
      .addOnSuccessListener(
          new OnSuccessListener<String>() {
            @Override
            public void onSuccess(List<IdentifiedLanguage> identifiedLanguages) {
              for (IdentifiedLanguage identifiedLanguage : identifiedLanguages) {
                String language = identifiedLanguage.getLanguageCode();
                float confidence = identifiedLanguage.getConfidence();
                Log.i(TAG, language + " (" + confidence + ")");
              }
            }
          })
      .addOnFailureListener(
          new OnFailureListener() {
            @Override
            public void onFailure(@NonNull Exception e) {
              // Model couldn’t be loaded or other internal error.
              // ...
            }
          });

If the call succeeds, a list of IdentifiedLanguage objects is passed to the success listener. From each object, you can get the language's BCP-47 code and the confidence that the string is in that language. See the complete list of supported languages. Note that these values indicate the confidence that the entire string is in the given language; ML Kit doesn't identify multiple languages in a single string.

By default, ML Kit returns only languages with confidence values of at least 0.01. You can change this threshold by passing a FirebaseLanguageIdentificationOptions object to getLanguageIdentification():

FirebaseLanguageIdentification languageIdentifier = FirebaseNaturalLanguage
        .getInstance()
        .getLanguageIdentification(
                new FirebaseLanguageIdentificationOptions.Builder()
                        .setIdentifyAllLanguagesConfidenceThreshold(0.5f)
                        .build());

If no language meets this threshold, the list will have one item, with the value und.

Next steps

See the ML Kit quickstart sample on GitHub for an example of this API in use.