Transcribe speech to text by using client libraries

This page shows you how to send a speech recognition request to Speech-to-Text in your favorite programming language using the Google Cloud Client Libraries.

Speech-to-Text enables easy integration of Google speech recognition technologies into developer applications. You can send audio data to the Speech-to-Text API, which then returns a text transcription of that audio file. For more information about the service, see Speech-to-Text basics.

Before you begin

  1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.
  2. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  3. Make sure that billing is enabled for your Google Cloud project.

  4. Enable the Speech-to-Text APIs.

    Enable the APIs

  5. Make sure that you have the following role or roles on the project: Cloud Speech Administrator

    Check for the roles

    1. In the Google Cloud console, go to the IAM page.

      Go to IAM
    2. Select the project.
    3. In the Principal column, find all rows that identify you or a group that you're included in. To learn which groups you're included in, contact your administrator.

    4. For all rows that specify or include you, check the Role colunn to see whether the list of roles includes the required roles.

    Grant the roles

    1. In the Google Cloud console, go to the IAM page.

      Go to IAM
    2. Select the project.
    3. Click Grant access.
    4. In the New principals field, enter your user identifier. This is typically the email address for a Google Account.

    5. In the Select a role list, select a role.
    6. To grant additional roles, click Add another role and add each additional role.
    7. Click Save.
  6. Install the Google Cloud CLI.
  7. To initialize the gcloud CLI, run the following command:

    gcloud init
  8. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  9. Make sure that billing is enabled for your Google Cloud project.

  10. Enable the Speech-to-Text APIs.

    Enable the APIs

  11. Make sure that you have the following role or roles on the project: Cloud Speech Administrator

    Check for the roles

    1. In the Google Cloud console, go to the IAM page.

      Go to IAM
    2. Select the project.
    3. In the Principal column, find all rows that identify you or a group that you're included in. To learn which groups you're included in, contact your administrator.

    4. For all rows that specify or include you, check the Role colunn to see whether the list of roles includes the required roles.

    Grant the roles

    1. In the Google Cloud console, go to the IAM page.

      Go to IAM
    2. Select the project.
    3. Click Grant access.
    4. In the New principals field, enter your user identifier. This is typically the email address for a Google Account.

    5. In the Select a role list, select a role.
    6. To grant additional roles, click Add another role and add each additional role.
    7. Click Save.
  12. Install the Google Cloud CLI.
  13. To initialize the gcloud CLI, run the following command:

    gcloud init
  14. Client libraries can use Application Default Credentials to easily authenticate with Google APIs and send requests to those APIs. With Application Default Credentials, you can test your application locally and deploy it without changing the underlying code. For more information, see Authenticate for using client libraries.

  15. If you're using a local shell, then create local authentication credentials for your user account:

    gcloud auth application-default login

    You don't need to do this if you're using Cloud Shell.

Also ensure you have installed the client library.

Make an audio transcription request

Use the following code to send a Recognize request to the Speech-to-Text API.

Java

// Imports the Google Cloud client library
import com.google.api.gax.longrunning.OperationFuture;
import com.google.cloud.speech.v2.AutoDetectDecodingConfig;
import com.google.cloud.speech.v2.CreateRecognizerRequest;
import com.google.cloud.speech.v2.OperationMetadata;
import com.google.cloud.speech.v2.RecognitionConfig;
import com.google.cloud.speech.v2.RecognizeRequest;
import com.google.cloud.speech.v2.RecognizeResponse;
import com.google.cloud.speech.v2.Recognizer;
import com.google.cloud.speech.v2.SpeechClient;
import com.google.cloud.speech.v2.SpeechRecognitionAlternative;
import com.google.cloud.speech.v2.SpeechRecognitionResult;
import com.google.protobuf.ByteString;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;
import java.util.List;
import java.util.concurrent.ExecutionException;

public class QuickstartSampleV2 {

  public static void main(String[] args) throws IOException, ExecutionException,
      InterruptedException {
    String projectId = "my-project-id";
    String filePath = "path/to/audioFile.raw";
    String recognizerId = "my-recognizer-id";
    quickstartSampleV2(projectId, filePath, recognizerId);
  }

  public static void quickstartSampleV2(String projectId, String filePath, String recognizerId)
      throws IOException, ExecutionException, InterruptedException {

    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (SpeechClient speechClient = SpeechClient.create()) {
      Path path = Paths.get(filePath);
      byte[] data = Files.readAllBytes(path);
      ByteString audioBytes = ByteString.copyFrom(data);

      String parent = String.format("projects/%s/locations/global", projectId);

      // First, create a recognizer
      Recognizer recognizer = Recognizer.newBuilder()
          .setModel("latest_long")
          .addLanguageCodes("en-US")
          .build();

      CreateRecognizerRequest createRecognizerRequest = CreateRecognizerRequest.newBuilder()
          .setParent(parent)
          .setRecognizerId(recognizerId)
          .setRecognizer(recognizer)
          .build();

      OperationFuture<Recognizer, OperationMetadata> operationFuture =
          speechClient.createRecognizerAsync(createRecognizerRequest);
      recognizer = operationFuture.get();

      // Next, create the transcription request
      RecognitionConfig recognitionConfig = RecognitionConfig.newBuilder()
          .setAutoDecodingConfig(AutoDetectDecodingConfig.newBuilder().build())
          .build();

      RecognizeRequest request = RecognizeRequest.newBuilder()
          .setConfig(recognitionConfig)
          .setRecognizer(recognizer.getName())
          .setContent(audioBytes)
          .build();

      RecognizeResponse response = speechClient.recognize(request);
      List<SpeechRecognitionResult> results = response.getResultsList();

      for (SpeechRecognitionResult result : results) {
        // There can be several alternative transcripts for a given chunk of speech. Just use the
        // first (most likely) one here.
        if (result.getAlternativesCount() > 0) {
          SpeechRecognitionAlternative alternative = result.getAlternativesList().get(0);
          System.out.printf("Transcription: %s%n", alternative.getTranscript());
        }
      }
    }
  }
}

Python

import os

from google.cloud.speech_v2 import SpeechClient
from google.cloud.speech_v2.types import cloud_speech

PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")


def quickstart_v2(audio_file: str) -> cloud_speech.RecognizeResponse:
    """Transcribe an audio file.
    Args:
        audio_file (str): Path to the local audio file to be transcribed.
    Returns:
        cloud_speech.RecognizeResponse: The response from the recognize request, containing
        the transcription results
    """
    # Reads a file as bytes
    with open(audio_file, "rb") as f:
        audio_content = f.read()

    # Instantiates a client
    client = SpeechClient()

    config = cloud_speech.RecognitionConfig(
        auto_decoding_config=cloud_speech.AutoDetectDecodingConfig(),
        language_codes=["en-US"],
        model="long",
    )

    request = cloud_speech.RecognizeRequest(
        recognizer=f"projects/{PROJECT_ID}/locations/global/recognizers/_",
        config=config,
        content=audio_content,
    )

    # Transcribes the audio into text
    response = client.recognize(request=request)

    for result in response.results:
        print(f"Transcript: {result.alternatives[0].transcript}")

    return response

You sent your first request to Speech-to-Text.

Clean up

To avoid incurring charges to your Google Cloud account for the resources used on this page, follow these steps.

  1. Optional: Revoke the authentication credentials that you created, and delete the local credential file.

    gcloud auth application-default revoke
  2. Optional: Revoke credentials from the gcloud CLI.

    gcloud auth revoke

Console

  • In the Google Cloud console, go to the Manage resources page.

    Go to Manage resources

  • In the project list, select the project that you want to delete, and then click Delete.
  • In the dialog, type the project ID, and then click Shut down to delete the project.
  • gcloud

    Delete a Google Cloud project:

    gcloud projects delete PROJECT_ID

    What's next