Transcribe short audio files

This page demonstrates how to transcribe a short audio file to text using synchronous speech recognition.

Synchronous speech recognition returns the recognized text for short audio (less than 60 seconds).

Audio content can be sent directly to Speech-to-Text from a local file, or Speech-to-Text can process audio content stored in a Cloud Storage bucket. See the quotas and limits page for limits on synchronous speech recognition requests.

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 the row that has your email address.

      If your email address isn't in that column, then you do not have any roles.

    4. In the Role column for the row with your email address, check 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 email address.
    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 the row that has your email address.

      If your email address isn't in that column, then you do not have any roles.

    4. In the Role column for the row with your email address, check 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 email address.
    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. Create local authentication credentials for your Google Account:

    gcloud auth application-default login

Also ensure you have installed the client library.

Perform synchronous speech recognition on a local file

Here is an example of performing synchronous speech recognition on a local audio file:

Python

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


def transcribe_file_v2(
    project_id: str,
    audio_file: str,
) -> cloud_speech.RecognizeResponse:
    # Instantiates a client
    client = SpeechClient()

    # Reads a file as bytes
    with open(audio_file, "rb") as f:
        content = f.read()

    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=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

Perform synchronous speech recognition on a remote file

For your convenience, Speech-to-Text API can perform synchronous speech recognition directly on an audio file located in Cloud Storage, without the need to send the contents of the audio file in the body of your request.

Speech-to-Text uses a service account to access your files in Cloud Storage. By default, the service account has access to Cloud Storage files in the same project.

The service account email address is the following:

service-PROJECT_NUMBER@gcp-sa-speech.iam.gserviceaccount.com

In order to transcribe Cloud Storage files in another project, you can give this service account the Speech-to-Text Service Agent role in the other project:

gcloud projects add-iam-policy-binding PROJECT_ID \
    --member=serviceAccount:service-PROJECT_NUMBER@gcp-sa-speech.iam.gserviceaccount.com \
    --role=roles/speech.serviceAgent

More information about project IAM policy is available at Manage access to projects, folders, and organizations.

You can also give the service account more granular access by giving it permission to a specific Cloud Storage bucket:

gsutil iam ch serviceAccount:service-PROJECT_NUMBER@gcp-sa-speech.iam.gserviceaccount.com:admin \
    gs://BUCKET_NAME

More information about managing access to Cloud Storage is available at Create and Manage access control lists in the Cloud Storage documentation.

Here is an example of performing synchronous speech recognition on a file located in Cloud Storage:

Python

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


def transcribe_gcs_v2(
    project_id: str,
    gcs_uri: str,
) -> cloud_speech.RecognizeResponse:
    """Transcribes audio from a Google Cloud Storage URI.

    Args:
        project_id: The GCP project ID.
        gcs_uri: The Google Cloud Storage URI.

    Returns:
        The RecognizeResponse.
    """
    # 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,
        uri=gcs_uri,
    )

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

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

    return response

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