Transcribe a local multi-lingual file (beta)

Transcribe a local audio file that includes more than one language.

Explore further

For detailed documentation that includes this code sample, see the following:

• Enable language recognition in Speech-to-Text

Code sample

Java

To learn how to install and use the client library for Cloud STT, see Cloud STT client libraries. For more information, see the Cloud STT Java API reference documentation.

To authenticate to Cloud STT, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

/**
 * Transcribe a local audio file with multi-language recognition
 *
 * @param fileName the path to the audio file
 */
public static void transcribeMultiLanguage(String fileName) throws Exception {
  Path path = Paths.get(fileName);
  // Get the contents of the local audio file
  byte[] content = Files.readAllBytes(path);

  try (SpeechClient speechClient = SpeechClient.create()) {

    RecognitionAudio recognitionAudio =
        RecognitionAudio.newBuilder().setContent(ByteString.copyFrom(content)).build();
    ArrayList<String> languageList = new ArrayList<>();
    languageList.add("es-ES");
    languageList.add("en-US");

    // Configure request to enable multiple languages
    RecognitionConfig config =
        RecognitionConfig.newBuilder()
            .setEncoding(AudioEncoding.LINEAR16)
            .setSampleRateHertz(16000)
            .setLanguageCode("ja-JP")
            .addAllAlternativeLanguageCodes(languageList)
            .build();
    // Perform the transcription request
    RecognizeResponse recognizeResponse = speechClient.recognize(config, recognitionAudio);

    // Print out the results
    for (SpeechRecognitionResult result : recognizeResponse.getResultsList()) {
      // There can be several alternative transcripts for a given chunk of speech. Just use the
      // first (most likely) one here.
      SpeechRecognitionAlternative alternative = result.getAlternatives(0);
      System.out.format("Transcript : %s\n\n", alternative.getTranscript());
    }
  }
}

Node.js

To learn how to install and use the client library for Cloud STT, see Cloud STT client libraries. For more information, see the Cloud STT Node.js API reference documentation.

To authenticate to Cloud STT, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

const fs = require('fs');

// Imports the Google Cloud client library
const speech = require('@google-cloud/speech').v1p1beta1;

// Creates a client
const client = new speech.SpeechClient();

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const fileName = 'Local path to audio file, e.g. /path/to/audio.raw';

const config = {
  encoding: 'LINEAR16',
  sampleRateHertz: 44100,
  languageCode: 'en-US',
  alternativeLanguageCodes: ['es-ES', 'en-US'],
};

const audio = {
  content: fs.readFileSync(fileName).toString('base64'),
};

const request = {
  config: config,
  audio: audio,
};

const [response] = await client.recognize(request);
const transcription = response.results
  .map(result => result.alternatives[0].transcript)
  .join('\n');
console.log(`Transcription: ${transcription}`);

Python

To learn how to install and use the client library for Cloud STT, see Cloud STT client libraries. For more information, see the Cloud STT Python API reference documentation.

To authenticate to Cloud STT, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

from google.cloud import speech_v1p1beta1 as speech

client = speech.SpeechClient()

speech_file = "resources/multi.wav"
first_lang = "en-US"
second_lang = "es"

with open(speech_file, "rb") as audio_file:
    content = audio_file.read()

audio = speech.RecognitionAudio(content=content)

config = speech.RecognitionConfig(
    encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
    sample_rate_hertz=44100,
    audio_channel_count=2,
    language_code=first_lang,
    alternative_language_codes=[second_lang],
)

print("Waiting for operation to complete...")
response = client.recognize(config=config, audio=audio)

for i, result in enumerate(response.results):
    alternative = result.alternatives[0]
    print("-" * 20)
    print(f"First alternative of result {i}: {alternative}")
    print(f"Transcript: {alternative.transcript}")

return response.results

What's next

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