docs-archive/apache-airflow-providers-google/8.4.0/_sources/_api/airflow/providers/google/cloud/operators/translate_speech/index.rst.txt

:py:mod:`airflow.providers.google.cloud.operators.translate_speech`
===================================================================

.. py:module:: airflow.providers.google.cloud.operators.translate_speech

.. autoapi-nested-parse::

   This module contains a Google Cloud Translate Speech operator.



Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   airflow.providers.google.cloud.operators.translate_speech.CloudTranslateSpeechOperator




.. py:class:: CloudTranslateSpeechOperator(*, audio, config, target_language, format_, source_language, model, project_id = None, gcp_conn_id = 'google_cloud_default', impersonation_chain = None, **kwargs)

   Bases: :py:obj:`airflow.models.BaseOperator`

   Recognizes speech in audio input and translates it.

   Note that it uses the first result from the recognition api response - the one with the highest confidence
   In order to see other possible results please use
   :ref:`howto/operator:CloudSpeechToTextRecognizeSpeechOperator`
   and
   :ref:`howto/operator:CloudTranslateTextOperator`
   separately

   .. seealso::
       For more information on how to use this operator, take a look at the guide:
       :ref:`howto/operator:CloudTranslateSpeechOperator`

   See https://cloud.google.com/translate/docs/translating-text

   Execute method returns string object with the translation

   This is a list of dictionaries queried value.
   Dictionary typically contains three keys (though not
   all will be present in all cases).

   * ``detectedSourceLanguage``: The detected language (as an
     ISO 639-1 language code) of the text.
   * ``translatedText``: The translation of the text into the
     target language.
   * ``input``: The corresponding input value.
   * ``model``: The model used to translate the text.

   Dictionary is set as XCom return value.

   :param audio: audio data to be recognized. See more:
       https://googleapis.github.io/google-cloud-python/latest/speech/gapic/v1/types.html#google.cloud.speech_v1.types.RecognitionAudio

   :param config: information to the recognizer that specifies how to process the request. See more:
       https://googleapis.github.io/google-cloud-python/latest/speech/gapic/v1/types.html#google.cloud.speech_v1.types.RecognitionConfig

   :param target_language: The language to translate results into. This is required by the API and defaults
       to the target language of the current instance.
       Check the list of available languages here: https://cloud.google.com/translate/docs/languages

   :param format_: (Optional) One of ``text`` or ``html``, to specify
       if the input text is plain text or HTML.

   :param source_language: (Optional) The language of the text to
       be translated.

   :param model: (Optional) The model used to translate the text, such
       as ``'base'`` or ``'nmt'``.

   :param project_id: Optional, Google Cloud Project ID where the Compute
       Engine Instance exists. If set to None or missing, the default project_id from the Google Cloud
       connection is used.

   :param gcp_conn_id: Optional, The connection ID used to connect to Google Cloud.
       Defaults to 'google_cloud_default'.

   :param impersonation_chain: Optional service account to impersonate using short-term
       credentials, or chained list of accounts required to get the access_token
       of the last account in the list, which will be impersonated in the request.
       If set as a string, the account must grant the originating account
       the Service Account Token Creator IAM role.
       If set as a sequence, the identities from the list must grant
       Service Account Token Creator IAM role to the directly preceding identity, with first
       account from the list granting this role to the originating account (templated).


   .. py:attribute:: template_fields
      :annotation: :Sequence[str] = ['target_language', 'format_', 'source_language', 'model', 'project_id', 'gcp_conn_id',...

      

   .. py:attribute:: operator_extra_links
      

      

   .. py:method:: execute(context)

      This is the main method to derive when creating an operator.
      Context is the same dictionary used as when rendering jinja templates.

      Refer to get_template_context for more context.