Reconocedores

La versión 2 de Speech-to-Text admite un recurso llamado Google Cloud recognizers. Los reconocedores representan la configuración de reconocimiento almacenada y reutilizable. Puedes usarlos para agrupar lógicamente transcripciones o tráfico de tu aplicación.

Antes de empezar

  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.

    Roles required to select or create a project

    • Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
    • Create a project: To create a project, you need the Project Creator (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

    Go to project selector

  3. Verify that billing is enabled for your Google Cloud project.

  4. Enable the Speech-to-Text APIs.

    Roles required to enable APIs

    To enable APIs, you need the Service Usage Admin IAM role (roles/serviceusage.serviceUsageAdmin), which contains the serviceusage.services.enable permission. Learn how to grant roles.

    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 column 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.

      Ir a IAM
    2. Selecciona el proyecto.
    3. Haz clic en Conceder acceso.
    4. En el campo Nuevos principales, introduce tu identificador de usuario. Normalmente, se trata de la dirección de correo de una cuenta de Google.

    5. En la lista Selecciona un rol, elige un rol.
    6. Para conceder más roles, haz clic en Añadir otro rol y añade cada rol adicional.
    7. Haz clic en Guardar.
  6. Install the Google Cloud CLI.

  7. Si utilizas un proveedor de identidades (IdP) externo, primero debes iniciar sesión en la CLI de gcloud con tu identidad federada.

  8. Para inicializar gcloud CLI, ejecuta el siguiente comando:

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

    Roles required to select or create a project

    • Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
    • Create a project: To create a project, you need the Project Creator (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

    Go to project selector

  10. Verify that billing is enabled for your Google Cloud project.

  11. Enable the Speech-to-Text APIs.

    Roles required to enable APIs

    To enable APIs, you need the Service Usage Admin IAM role (roles/serviceusage.serviceUsageAdmin), which contains the serviceusage.services.enable permission. Learn how to grant roles.

    Enable the APIs

  12. 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 column 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.

      Ir a IAM
    2. Selecciona el proyecto.
    3. Haz clic en Conceder acceso.
    4. En el campo Nuevos principales, introduce tu identificador de usuario. Normalmente, se trata de la dirección de correo de una cuenta de Google.

    5. En la lista Selecciona un rol, elige un rol.
    6. Para conceder más roles, haz clic en Añadir otro rol y añade cada rol adicional.
    7. Haz clic en Guardar.
  13. Install the Google Cloud CLI.

  14. Si utilizas un proveedor de identidades (IdP) externo, primero debes iniciar sesión en la CLI de gcloud con tu identidad federada.

  15. Para inicializar gcloud CLI, ejecuta el siguiente comando:

    gcloud init
  16. Las bibliotecas de cliente pueden usar las credenciales predeterminadas de la aplicación para autenticarse fácilmente en las APIs de Google y enviar solicitudes a esas APIs. Con las credenciales predeterminadas de la aplicación, puedes probar tu aplicación de forma local e implementarla sin cambiar el código subyacente. Para obtener más información, consulta el artículo Autenticarse para usar bibliotecas de cliente.

  17. 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.

    If an authentication error is returned, and you are using an external identity provider (IdP), confirm that you have signed in to the gcloud CLI with your federated identity.

  18. También debes instalar la biblioteca de cliente.

    Información sobre los reconocedores

    Los reconocedores son configuraciones de reconocimiento reutilizables y configurables. Crear reconocedores con configuraciones de reconocimiento que se usen con frecuencia ayuda a simplificar y reducir el tamaño de las solicitudes de reconocimiento.

    El elemento principal de un reconocedor es su configuración predeterminada. Esta es la configuración de cada solicitud de reconocimiento que realiza este reconocedor. Puedes anular este valor predeterminado por solicitud. Mantener la configuración predeterminada de las funciones que necesites en las solicitudes de un determinado reconocedor y, al mismo tiempo, anular funciones específicas para solicitudes concretas.

    Reutiliza los reconocedores tantas veces como sea posible. Crear una por cada solicitud aumenta considerablemente la latencia de tu aplicación y consume tus cuotas de recursos. Crea estos elementos con poca frecuencia durante la integración y la configuración, y luego reutilízalos para las solicitudes de reconocimiento.

    Crear reconocedores

    A continuación, se muestra un ejemplo de cómo crear un reconocedor que se puede usar para enviar solicitudes de reconocimiento:

    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 create_recognizer(recognizer_id: str) -> cloud_speech.Recognizer:
        """Сreates a recognizer with an unique ID and default recognition configuration.
        Args:
            recognizer_id (str): The unique identifier for the recognizer to be created.
        Returns:
            cloud_speech.Recognizer: The created recognizer object with configuration.
        """
        # Instantiates a client
        client = SpeechClient()
    
        request = cloud_speech.CreateRecognizerRequest(
            parent=f"projects/{PROJECT_ID}/locations/global",
            recognizer_id=recognizer_id,
            recognizer=cloud_speech.Recognizer(
                default_recognition_config=cloud_speech.RecognitionConfig(
                    language_codes=["en-US"], model="long"
                ),
            ),
        )
        # Sends the request to create a recognizer and waits for the operation to complete
        operation = client.create_recognizer(request=request)
        recognizer = operation.result()
    
        print("Created Recognizer:", recognizer.name)
        return recognizer
    
    

    Usar un reconocedor ya creado para enviar solicitudes

    A continuación, se muestra un ejemplo de cómo enviar varias solicitudes de reconocimiento usando el mismo reconocedor:

    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 transcribe_reuse_recognizer(
        audio_file: str,
        recognizer_id: str,
    ) -> cloud_speech.RecognizeResponse:
        """Transcribe an audio file using an existing recognizer.
        Args:
            audio_file (str): Path to the local audio file to be transcribed.
                Example: "resources/audio.wav"
            recognizer_id (str): The ID of the existing recognizer to be used for transcription.
        Returns:
            cloud_speech.RecognizeResponse: The response containing the transcription results.
        """
        # Instantiates a client
        client = SpeechClient()
    
        # Reads a file as bytes
        with open(audio_file, "rb") as f:
            audio_content = f.read()
    
        request = cloud_speech.RecognizeRequest(
            recognizer=f"projects/{PROJECT_ID}/locations/global/recognizers/{recognizer_id}",
            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
    
    

    Habilitar funciones en un reconocedor

    Los reconocedores se pueden usar para habilitar varias funciones de reconocimiento, como la puntuación automática o el filtrado de palabras malsonantes.

    A continuación, se muestra un ejemplo de cómo habilitar la puntuación automática en un reconocedor, lo que permite habilitar la puntuación automática en la solicitud de reconocimiento mediante este reconocedor:

    Python

    
    from google.cloud.speech_v2 import SpeechClient
    from google.cloud.speech_v2.types import cloud_speech
    
    from google.api_core.exceptions import NotFound
    
    # Instantiates a client
    client = SpeechClient()
    
    # TODO(developer): Update and un-comment below line
    # PROJECT_ID = "your-project-id"
    # recognizer_id = "id-recognizer"
    recognizer_name = (
        f"projects/{PROJECT_ID}/locations/global/recognizers/{recognizer_id}"
    )
    try:
        # Use an existing recognizer
        recognizer = client.get_recognizer(name=recognizer_name)
        print("Using existing Recognizer:", recognizer.name)
    except NotFound:
        # Create a new recognizer
        request = cloud_speech.CreateRecognizerRequest(
            parent=f"projects/{PROJECT_ID}/locations/global",
            recognizer_id=recognizer_id,
            recognizer=cloud_speech.Recognizer(
                default_recognition_config=cloud_speech.RecognitionConfig(
                    auto_decoding_config=cloud_speech.AutoDetectDecodingConfig(),
                    language_codes=["en-US"],
                    model="latest_long",
                    features=cloud_speech.RecognitionFeatures(
                        enable_automatic_punctuation=True,
                    ),
                ),
            ),
        )
        operation = client.create_recognizer(request=request)
        recognizer = operation.result()
        print("Created Recognizer:", recognizer.name)
    
    # Reads a file as bytes
    with open(audio_file, "rb") as f:
        audio_content = f.read()
    
    request = cloud_speech.RecognizeRequest(
        recognizer=f"projects/{PROJECT_ID}/locations/global/recognizers/{recognizer_id}",
        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}")
    

    Anular las funciones del reconocedor en las solicitudes de reconocimiento

    A continuación, se muestra un ejemplo de cómo habilitar varias funciones en un reconocedor, pero inhabilitar la puntuación automática para esta solicitud de reconocimiento:

    Python

    import os
    
    from google.cloud.speech_v2 import SpeechClient
    from google.cloud.speech_v2.types import cloud_speech
    from google.protobuf.field_mask_pb2 import FieldMask
    
    PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
    
    
    def transcribe_override_recognizer(
        audio_file: str,
        recognizer_id: str,
    ) -> cloud_speech.RecognizeResponse:
        """Transcribe an audio file using an existing recognizer with overridden settings for the recognition request.
        Args:
            audio_file (str): Path to the local audio file to be transcribed.
                Example: "resources/audio.wav"
            recognizer_id (str): The unique ID of the recognizer to be used for transcription.
        Returns:
            cloud_speech.RecognizeResponse: The response containing the transcription results.
        """
        # Instantiates a client
        client = SpeechClient()
    
        request = cloud_speech.CreateRecognizerRequest(
            parent=f"projects/{PROJECT_ID}/locations/global",
            recognizer_id=recognizer_id,
            recognizer=cloud_speech.Recognizer(
                default_recognition_config=cloud_speech.RecognitionConfig(
                    auto_decoding_config=cloud_speech.AutoDetectDecodingConfig(),
                    language_codes=["en-US"],
                    model="latest_long",
                    features=cloud_speech.RecognitionFeatures(
                        enable_automatic_punctuation=True,
                        enable_word_time_offsets=True,
                    ),
                ),
            ),
        )
    
        operation = client.create_recognizer(request=request)
        recognizer = operation.result()
    
        print("Created Recognizer:", recognizer.name)
    
        # Reads a file as bytes
        with open(audio_file, "rb") as f:
            audio_content = f.read()
    
        request = cloud_speech.RecognizeRequest(
            recognizer=f"projects/{PROJECT_ID}/locations/global/recognizers/{recognizer_id}",
            config=cloud_speech.RecognitionConfig(
                features=cloud_speech.RecognitionFeatures(
                    enable_word_time_offsets=False,
                ),
            ),
            config_mask=FieldMask(paths=["features.enable_word_time_offsets"]),
            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
    
    

    Enviar solicitudes sin reconocedores

    Los reconocedores son opcionales en las solicitudes de reconocimiento. Para hacer una solicitud sin un reconocedor, solo tienes que usar el ID de recurso del reconocedor _ en la ubicación en la que hagas la solicitud. A continuación se muestra un ejemplo:

    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
    
    

    Limpieza

    Para evitar que se apliquen cargos en tu cuenta de Google Cloud por los recursos utilizados en esta página, sigue estos pasos.

    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

    Consola

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

    Go to Manage resources

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

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

    Go to Manage resources

  24. In the project list, select the project that you want to delete, and then click Delete.
  25. In the dialog, type the project ID, and then click Shut down to delete the project.
  26. Siguientes pasos