Transcribe a file with word-level confidence (beta)

Transcribe an audio file, returning the confidence level for each word.

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

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 word level confidence
 *
 * @param fileName the path to the local audio file
 */
public static void transcribeWordLevelConfidence(String fileName) throws Exception {
  Path path = Paths.get(fileName);
  byte[] content = Files.readAllBytes(path);

  try (SpeechClient speechClient = SpeechClient.create()) {
    RecognitionAudio recognitionAudio =
        RecognitionAudio.newBuilder().setContent(ByteString.copyFrom(content)).build();
    // Configure request to enable word level confidence
    RecognitionConfig config =
        RecognitionConfig.newBuilder()
            .setEncoding(AudioEncoding.LINEAR16)
            .setSampleRateHertz(16000)
            .setLanguageCode("en-US")
            .setEnableWordConfidence(true)
            .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", alternative.getTranscript());
      System.out.format(
          "First Word and Confidence : %s %s \n",
          alternative.getWords(0).getWord(), alternative.getWords(0).getConfidence());
    }
  }
}

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: 'FLAC',
  sampleRateHertz: 16000,
  languageCode: 'en-US',
  enableWordConfidence: true,
};

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

console.log('Word-Level-Confidence:');
const words = response.results.map(result => result.alternatives[0]);
words[0].words.forEach(a => {
  console.log(` word: ${a.word}, confidence: ${a.confidence}`);
});

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/Google_Gnome.wav"

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=16000,
    language_code="en-US",
    enable_word_confidence=True,
)

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}")
    print(f"Transcript: {alternative.transcript}")
    print(
        "First Word and Confidence: ({}, {})".format(
            alternative.words[0].word, alternative.words[0].confidence
        )
    )

return response.results

What's next

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