aws

# WARNING: DO NOT EDIT, AUTO-GENERATED CODE!
# See https://github.com/aws-beam/aws-codegen for more details.

defmodule AWS.Transcribe do
  @moduledoc """
  Operations and objects for transcribing speech to text.
  """

  alias AWS.Client
  alias AWS.Request

  def metadata do
    %AWS.ServiceMetadata{
      abbreviation: nil,
      api_version: "2017-10-26",
      content_type: "application/x-amz-json-1.1",
      credential_scope: nil,
      endpoint_prefix: "transcribe",
      global?: false,
      protocol: "json",
      service_id: "Transcribe",
      signature_version: "v4",
      signing_name: "transcribe",
      target_prefix: "Transcribe"
    }
  end

  @doc """
  Creates an analytics category.

  Amazon Transcribe applies the conditions specified by your analytics categories
  to your call analytics jobs. For each analytics category, you specify one or
  more rules. For example, you can specify a rule that the customer sentiment was
  neutral or negative within that category. If you start a call analytics job,
  Amazon Transcribe applies the category to the analytics job that you've
  specified.
  """
  def create_call_analytics_category(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "CreateCallAnalyticsCategory", input, options)
  end

  @doc """
  Creates a new custom language model.

  Use Amazon S3 prefixes to provide the location of your input files. The time it
  takes to create your model depends on the size of your training data.
  """
  def create_language_model(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "CreateLanguageModel", input, options)
  end

  @doc """
  Creates a new custom vocabulary that you can use to modify how Amazon Transcribe
  Medical transcribes your audio file.
  """
  def create_medical_vocabulary(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "CreateMedicalVocabulary", input, options)
  end

  @doc """
  Creates a new custom vocabulary that you can use to change the way Amazon
  Transcribe handles transcription of an audio file.
  """
  def create_vocabulary(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "CreateVocabulary", input, options)
  end

  @doc """
  Creates a new vocabulary filter that you can use to filter words, such as
  profane words, from the output of a transcription job.
  """
  def create_vocabulary_filter(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "CreateVocabularyFilter", input, options)
  end

  @doc """
  Deletes a call analytics category using its name.
  """
  def delete_call_analytics_category(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "DeleteCallAnalyticsCategory", input, options)
  end

  @doc """
  Deletes a call analytics job using its name.
  """
  def delete_call_analytics_job(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "DeleteCallAnalyticsJob", input, options)
  end

  @doc """
  Deletes a custom language model using its name.
  """
  def delete_language_model(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "DeleteLanguageModel", input, options)
  end

  @doc """
  Deletes a transcription job generated by Amazon Transcribe Medical and any
  related information.
  """
  def delete_medical_transcription_job(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "DeleteMedicalTranscriptionJob", input, options)
  end

  @doc """
  Deletes a vocabulary from Amazon Transcribe Medical.
  """
  def delete_medical_vocabulary(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "DeleteMedicalVocabulary", input, options)
  end

  @doc """
  Deletes a previously submitted transcription job along with any other generated
  results such as the transcription, models, and so on.
  """
  def delete_transcription_job(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "DeleteTranscriptionJob", input, options)
  end

  @doc """
  Deletes a vocabulary from Amazon Transcribe.
  """
  def delete_vocabulary(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "DeleteVocabulary", input, options)
  end

  @doc """
  Removes a vocabulary filter.
  """
  def delete_vocabulary_filter(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "DeleteVocabularyFilter", input, options)
  end

  @doc """
  Gets information about a single custom language model.

  Use this information to see details about the language model in your Amazon Web
  Services account. You can also see whether the base language model used to
  create your custom language model has been updated. If Amazon Transcribe has
  updated the base model, you can create a new custom language model using the
  updated base model. If the language model wasn't created, you can use this
  operation to understand why Amazon Transcribe couldn't create it.
  """
  def describe_language_model(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "DescribeLanguageModel", input, options)
  end

  @doc """
  Retrieves information about a call analytics category.
  """
  def get_call_analytics_category(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "GetCallAnalyticsCategory", input, options)
  end

  @doc """
  Returns information about a call analytics job.

  To see the status of the job, check the `CallAnalyticsJobStatus` field. If the
  status is `COMPLETED`, the job is finished and you can find the results at the
  location specified in the `TranscriptFileUri` field. If you enable personally
  identifiable information (PII) redaction, the redacted transcript appears in the
  `RedactedTranscriptFileUri` field.
  """
  def get_call_analytics_job(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "GetCallAnalyticsJob", input, options)
  end

  @doc """
  Returns information about a transcription job from Amazon Transcribe Medical.

  To see the status of the job, check the `TranscriptionJobStatus` field. If the
  status is `COMPLETED`, the job is finished. You find the results of the
  completed job in the `TranscriptFileUri` field.
  """
  def get_medical_transcription_job(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "GetMedicalTranscriptionJob", input, options)
  end

  @doc """
  Retrieves information about a medical vocabulary.
  """
  def get_medical_vocabulary(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "GetMedicalVocabulary", input, options)
  end

  @doc """
  Returns information about a transcription job.

  To see the status of the job, check the `TranscriptionJobStatus` field. If the
  status is `COMPLETED`, the job is finished and you can find the results at the
  location specified in the `TranscriptFileUri` field. If you enable content
  redaction, the redacted transcript appears in `RedactedTranscriptFileUri`.
  """
  def get_transcription_job(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "GetTranscriptionJob", input, options)
  end

  @doc """
  Gets information about a vocabulary.
  """
  def get_vocabulary(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "GetVocabulary", input, options)
  end

  @doc """
  Returns information about a vocabulary filter.
  """
  def get_vocabulary_filter(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "GetVocabularyFilter", input, options)
  end

  @doc """
  Provides more information about the call analytics categories that you've
  created.

  You can use the information in this list to find a specific category. You can
  then use the operation to get more information about it.
  """
  def list_call_analytics_categories(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "ListCallAnalyticsCategories", input, options)
  end

  @doc """
  List call analytics jobs with a specified status or substring that matches their
  names.
  """
  def list_call_analytics_jobs(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "ListCallAnalyticsJobs", input, options)
  end

  @doc """
  Provides more information about the custom language models you've created.

  You can use the information in this list to find a specific custom language
  model. You can then use the operation to get more information about it.
  """
  def list_language_models(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "ListLanguageModels", input, options)
  end

  @doc """
  Lists medical transcription jobs with a specified status or substring that
  matches their names.
  """
  def list_medical_transcription_jobs(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "ListMedicalTranscriptionJobs", input, options)
  end

  @doc """
  Returns a list of vocabularies that match the specified criteria.

  If you don't enter a value in any of the request parameters, returns the entire
  list of vocabularies.
  """
  def list_medical_vocabularies(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "ListMedicalVocabularies", input, options)
  end

  @doc """
  Lists all tags associated with a given transcription job, vocabulary, or
  resource.
  """
  def list_tags_for_resource(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "ListTagsForResource", input, options)
  end

  @doc """
  Lists transcription jobs with the specified status.
  """
  def list_transcription_jobs(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "ListTranscriptionJobs", input, options)
  end

  @doc """
  Returns a list of vocabularies that match the specified criteria.

  If no criteria are specified, returns the entire list of vocabularies.
  """
  def list_vocabularies(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "ListVocabularies", input, options)
  end

  @doc """
  Gets information about vocabulary filters.
  """
  def list_vocabulary_filters(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "ListVocabularyFilters", input, options)
  end

  @doc """
  Starts an asynchronous analytics job that not only transcribes the audio
  recording of a caller and agent, but also returns additional insights.

  These insights include how quickly or loudly the caller or agent was speaking.
  To retrieve additional insights with your analytics jobs, create categories. A
  category is a way to classify analytics jobs based on attributes, such as a
  customer's sentiment or a particular phrase being used during the call. For more
  information, see the operation.
  """
  def start_call_analytics_job(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "StartCallAnalyticsJob", input, options)
  end

  @doc """
  Starts a batch job to transcribe medical speech to text.
  """
  def start_medical_transcription_job(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "StartMedicalTranscriptionJob", input, options)
  end

  @doc """
  Starts an asynchronous job to transcribe speech to text.
  """
  def start_transcription_job(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "StartTranscriptionJob", input, options)
  end

  @doc """
  Tags an Amazon Transcribe resource with the given list of tags.
  """
  def tag_resource(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "TagResource", input, options)
  end

  @doc """
  Removes specified tags from a specified Amazon Transcribe resource.
  """
  def untag_resource(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "UntagResource", input, options)
  end

  @doc """
  Updates the call analytics category with new values.

  The `UpdateCallAnalyticsCategory` operation overwrites all of the existing
  information with the values that you provide in the request.
  """
  def update_call_analytics_category(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "UpdateCallAnalyticsCategory", input, options)
  end

  @doc """
  Updates a vocabulary with new values that you provide in a different text file
  from the one you used to create the vocabulary.

  The `UpdateMedicalVocabulary` operation overwrites all of the existing
  information with the values that you provide in the request.
  """
  def update_medical_vocabulary(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "UpdateMedicalVocabulary", input, options)
  end

  @doc """
  Updates an existing vocabulary with new values.

  The `UpdateVocabulary` operation overwrites all of the existing information with
  the values that you provide in the request.
  """
  def update_vocabulary(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "UpdateVocabulary", input, options)
  end

  @doc """
  Updates a vocabulary filter with a new list of filtered words.
  """
  def update_vocabulary_filter(%Client{} = client, input, options \\ []) do
    Request.request_post(client, metadata(), "UpdateVocabularyFilter", input, options)
  end
end