start_medical_transcription_job async ¶

async def start_medical_transcription_job(
    self,
    medical_transcription_job_name: "capo_transcribe.types.transcription_job_name.TranscriptionJobName",
    language_code: "capo_transcribe.types.language_code.LanguageCode",
    media: "capo_transcribe.types.media.Media",
    output_bucket_name: "capo_transcribe.types.output_bucket_name.OutputBucketName",
    specialty: "capo_transcribe.types.specialty.Specialty",
    type: "capo_transcribe.types.type.Type",
    *,
    config_overrides: Optional[AsyncTranscribeClientConfig] = None,
    media_sample_rate_hertz: Optional[
        "capo_transcribe.types.medical_media_sample_rate_hertz.MedicalMediaSampleRateHertz"
    ] = None,
    media_format: Optional["capo_transcribe.types.media_format.MediaFormat"] = None,
    output_key: Optional["capo_transcribe.types.output_key.OutputKey"] = None,
    output_encryption_kms_key_id: Optional[
        "capo_transcribe.types.kms_key_id.KMSKeyId"
    ] = None,
    kms_encryption_context: Optional[
        "capo_transcribe.types.kms_encryption_context_map.KMSEncryptionContextMap"
    ] = None,
    settings: Optional[
        "capo_transcribe.types.medical_transcription_setting.MedicalTranscriptionSetting"
    ] = None,
    content_identification_type: Optional[
        "capo_transcribe.types.medical_content_identification_type.MedicalContentIdentificationType"
    ] = None,
    tags: Optional["capo_transcribe.types.tag_list.TagList"] = None,
) -> "capo_transcribe.types.start_medical_transcription_job_response.StartMedicalTranscriptionJobResponse":
    """<p>Transcribes the audio from a medical dictation or conversation and applies any additional Request Parameters you choose to include in your request.</p> <p>In addition to many standard transcription features, Amazon Transcribe Medical provides you with a robust medical vocabulary and, optionally, content identification, which adds flags to personal health information (PHI). To learn more about these features, refer to <a href="https://docs.aws.amazon.com/transcribe/latest/dg/how-it-works-med.html">How Amazon Transcribe Medical works</a>.</p> <p>To make a <code>StartMedicalTranscriptionJob</code> request, you must first upload your media file into an Amazon S3 bucket; you can then specify the Amazon S3 location of the file using the <code>Media</code> parameter.</p> <p>You must include the following parameters in your <code>StartMedicalTranscriptionJob</code> request:</p> <ul> <li> <p> <code>region</code>: The Amazon Web Services Region where you are making your request. For a list of Amazon Web Services Regions supported with Amazon Transcribe, refer to <a href="https://docs.aws.amazon.com/general/latest/gr/transcribe.html">Amazon Transcribe endpoints and quotas</a>.</p> </li> <li> <p> <code>MedicalTranscriptionJobName</code>: A custom name you create for your transcription job that is unique within your Amazon Web Services account.</p> </li> <li> <p> <code>Media</code> (<code>MediaFileUri</code>): The Amazon S3 location of your media file.</p> </li> <li> <p> <code>LanguageCode</code>: This must be <code>en-US</code>.</p> </li> <li> <p> <code>OutputBucketName</code>: The Amazon S3 bucket where you want your transcript stored. If you want your output stored in a sub-folder of this bucket, you must also include <code>OutputKey</code>.</p> </li> <li> <p> <code>Specialty</code>: This must be <code>PRIMARYCARE</code>.</p> </li> <li> <p> <code>Type</code>: Choose whether your audio is a conversation or a dictation.</p> </li> </ul>

    Args:
        medical_transcription_job_name: <p>A unique name, chosen by you, for your medical transcription job. The name that you specify is also used as the default name of your transcription output file. If you want to specify a different name for your transcription output, use the <code>OutputKey</code> parameter.</p> <p>This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account. If you try to create a new job with the same name as an existing job, you get a <code>ConflictException</code> error.</p>
        language_code: <p>The language code that represents the language spoken in the input media file. US English (<code>en-US</code>) is the only valid value for medical transcription jobs. Any other value you enter for language code results in a <code>BadRequestException</code> error.</p>
        media_sample_rate_hertz: <p>The sample rate, in hertz, of the audio track in your input media file.</p> <p>If you do not specify the media sample rate, Amazon Transcribe Medical determines it for you. If you specify the sample rate, it must match the rate detected by Amazon Transcribe Medical; if there's a mismatch between the value that you specify and the value detected, your job fails. Therefore, in most cases, it's advised to omit <code>MediaSampleRateHertz</code> and let Amazon Transcribe Medical determine the sample rate.</p>
        media_format: <p>Specify the format of your input media file.</p>
        output_bucket_name: <p>The name of the Amazon S3 bucket where you want your medical transcription output stored. Do not include the <code>S3://</code> prefix of the specified bucket.</p> <p>If you want your output to go to a sub-folder of this bucket, specify it using the <code>OutputKey</code> parameter; <code>OutputBucketName</code> only accepts the name of a bucket.</p> <p>For example, if you want your output stored in <code>S3://DOC-EXAMPLE-BUCKET</code>, set <code>OutputBucketName</code> to <code>DOC-EXAMPLE-BUCKET</code>. However, if you want your output stored in <code>S3://DOC-EXAMPLE-BUCKET/test-files/</code>, set <code>OutputBucketName</code> to <code>DOC-EXAMPLE-BUCKET</code> and <code>OutputKey</code> to <code>test-files/</code>.</p> <p>Note that Amazon Transcribe must have permission to use the specified location. You can change Amazon S3 permissions using the <a href="https://console.aws.amazon.com/s3">Amazon Web Services Management Console</a>. See also <a href="https://docs.aws.amazon.com/transcribe/latest/dg/security_iam_id-based-policy-examples.html#auth-role-iam-user">Permissions Required for IAM User Roles</a>.</p>
        output_key: <p>Use in combination with <code>OutputBucketName</code> to specify the output location of your transcript and, optionally, a unique name for your output file. The default name for your transcription output is the same as the name you specified for your medical transcription job (<code>MedicalTranscriptionJobName</code>).</p> <p>Here are some examples of how you can use <code>OutputKey</code>:</p> <ul> <li> <p>If you specify 'DOC-EXAMPLE-BUCKET' as the <code>OutputBucketName</code> and 'my-transcript.json' as the <code>OutputKey</code>, your transcription output path is <code>s3://DOC-EXAMPLE-BUCKET/my-transcript.json</code>.</p> </li> <li> <p>If you specify 'my-first-transcription' as the <code>MedicalTranscriptionJobName</code>, 'DOC-EXAMPLE-BUCKET' as the <code>OutputBucketName</code>, and 'my-transcript' as the <code>OutputKey</code>, your transcription output path is <code>s3://DOC-EXAMPLE-BUCKET/my-transcript/my-first-transcription.json</code>.</p> </li> <li> <p>If you specify 'DOC-EXAMPLE-BUCKET' as the <code>OutputBucketName</code> and 'test-files/my-transcript.json' as the <code>OutputKey</code>, your transcription output path is <code>s3://DOC-EXAMPLE-BUCKET/test-files/my-transcript.json</code>.</p> </li> <li> <p>If you specify 'my-first-transcription' as the <code>MedicalTranscriptionJobName</code>, 'DOC-EXAMPLE-BUCKET' as the <code>OutputBucketName</code>, and 'test-files/my-transcript' as the <code>OutputKey</code>, your transcription output path is <code>s3://DOC-EXAMPLE-BUCKET/test-files/my-transcript/my-first-transcription.json</code>.</p> </li> </ul> <p>If you specify the name of an Amazon S3 bucket sub-folder that doesn't exist, one is created for you.</p>
        output_encryption_kms_key_id: <p>The Amazon Resource Name (ARN) of a KMS key that you want to use to encrypt your medical transcription output.</p> <p>KMS key ARNs have the format <code>arn:partition:kms:region:account:key/key-id</code>. For example: <code>arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab</code>. For more information, see <a href="https://docs.aws.amazon.com/kms/latest/developerguide/concepts.html#key-id-key-ARN"> KMS key ARNs</a>.</p> <p>If you do not specify an encryption key, your output is encrypted with the default Amazon S3 key (SSE-S3).</p> <p>Note that the role making the request and the role specified in the <code>DataAccessRoleArn</code> request parameter (if present) must have permission to use the specified KMS key.</p>
        kms_encryption_context: <p>A map of plain text, non-secret key:value pairs, known as encryption context pairs, that provide an added layer of security for your data. For more information, see <a href="https://docs.aws.amazon.com/transcribe/latest/dg/key-management.html#kms-context">KMS encryption context</a> and <a href="https://docs.aws.amazon.com/transcribe/latest/dg/symmetric-asymmetric.html">Asymmetric keys in KMS</a>.</p>
        settings: <p>Specify additional optional settings in your request, including channel identification, alternative transcriptions, and speaker partitioning. You can use that to apply custom vocabularies to your transcription job.</p>
        content_identification_type: <p>Labels all personal health information (PHI) identified in your transcript. For more information, see <a href="https://docs.aws.amazon.com/transcribe/latest/dg/phi-id.html">Identifying personal health information (PHI) in a transcription</a>.</p>
        specialty: <p>Specify the predominant medical specialty represented in your media. For batch transcriptions, <code>PRIMARYCARE</code> is the only valid value. If you require additional specialties, refer to .</p>
        type: <p>Specify whether your input media contains only one person (<code>DICTATION</code>) or contains a conversation between two people (<code>CONVERSATION</code>).</p> <p>For example, <code>DICTATION</code> could be used for a medical professional wanting to transcribe voice memos; <code>CONVERSATION</code> could be used for transcribing the doctor-patient dialogue during the patient's office visit.</p>
        tags: <p>Adds one or more custom tags, each in the form of a key:value pair, to a new medical transcription job at the time you start this new job.</p> <p>To learn more about using tags with Amazon Transcribe, refer to <a href="https://docs.aws.amazon.com/transcribe/latest/dg/tagging.html">Tagging resources</a>.</p>

    Raises:
        capo_transcribe.errors.bad_request_exception.BadRequestException: <p>Your request didn't pass one or more validation tests. This can occur when the entity you're trying to delete doesn't exist or if it's in a non-terminal state (such as <code>IN PROGRESS</code>). See the exception message field for more information.</p>
        capo_transcribe.errors.conflict_exception.ConflictException: <p>A resource already exists with this name. Resource names must be unique within an Amazon Web Services account.</p>
        capo_transcribe.errors.internal_failure_exception.InternalFailureException: <p>There was an internal error. Check the error message, correct the issue, and try your request again.</p>
        capo_transcribe.errors.limit_exceeded_exception.LimitExceededException: <p>You've either sent too many requests or your input file is too long. Wait before retrying your request, or use a smaller file and try your request again.</p>
        capo_transcribe.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_transcribe.types.start_medical_transcription_job_request.StartMedicalTranscriptionJobRequest]",
    ) -> AsyncOperationResponse[
        "capo_transcribe.types.start_medical_transcription_job_response.StartMedicalTranscriptionJobResponse"
    ]:
        import capo_transcribe._operations.transcribe.start_medical_transcription_job

        (
            output,
            http_response,
        ) = await capo_transcribe._operations.transcribe.start_medical_transcription_job.async_start_medical_transcription_job(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("StartMedicalTranscriptionJob")
    )
    input_: capo_transcribe.types.start_medical_transcription_job_request.StartMedicalTranscriptionJobRequest = {
        "medical_transcription_job_name": medical_transcription_job_name,
        "language_code": language_code,
        "media": media,
        "output_bucket_name": output_bucket_name,
        "specialty": specialty,
        "type": type,
    }
    if media_sample_rate_hertz is not None:
        input_["media_sample_rate_hertz"] = media_sample_rate_hertz
    if media_format is not None:
        input_["media_format"] = media_format
    if output_key is not None:
        input_["output_key"] = output_key
    if output_encryption_kms_key_id is not None:
        input_["output_encryption_kms_key_id"] = output_encryption_kms_key_id
    if kms_encryption_context is not None:
        input_["kms_encryption_context"] = kms_encryption_context
    if settings is not None:
        input_["settings"] = settings
    if content_identification_type is not None:
        input_["content_identification_type"] = content_identification_type
    if tags is not None:
        input_["tags"] = tags

    response = await aexecute_pipeline(
        AsyncOperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    await response.response.aclose()
    return response.output