AWS CLI Command Reference

[ aws . transcribe ]

start-transcription-job

Description

Transcribes the audio from a media file and applies any additional Request Parameters you choose to include in your request.

To make a StartTranscriptionJob 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 Media parameter.

You must include the following parameters in your StartTranscriptionJob request:

  • region : 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 Amazon Transcribe endpoints and quotas .

  • TranscriptionJobName : A custom name you create for your transcription job that is unique within your Amazon Web Services account.

  • Media (MediaFileUri ): The Amazon S3 location of your media file.

  • One of LanguageCode , IdentifyLanguage , or IdentifyMultipleLanguages : If you know the language of your media file, specify it using the LanguageCode parameter; you can find all valid language codes in the Supported languages table. If you don’t know the languages spoken in your media, use either IdentifyLanguage or IdentifyMultipleLanguages and let Amazon Transcribe identify the languages for you.

See also: AWS API Documentation

Synopsis

  start-transcription-job
--transcription-job-name <value>
[--language-code <value>]
[--media-sample-rate-hertz <value>]
[--media-format <value>]
--media <value>
[--output-bucket-name <value>]
[--output-key <value>]
[--output-encryption-kms-key-id <value>]
[--kms-encryption-context <value>]
[--settings <value>]
[--model-settings <value>]
[--job-execution-settings <value>]
[--content-redaction <value>]
[--identify-language | --no-identify-language]
[--identify-multiple-languages | --no-identify-multiple-languages]
[--language-options <value>]
[--subtitles <value>]
[--tags <value>]
[--language-id-settings <value>]
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
[--debug]
[--endpoint-url <value>]
[--no-verify-ssl]
[--no-paginate]
[--output <value>]
[--query <value>]
[--profile <value>]
[--region <value>]
[--version <value>]
[--color <value>]
[--no-sign-request]
[--ca-bundle <value>]
[--cli-read-timeout <value>]
[--cli-connect-timeout <value>]
[--cli-binary-format <value>]
[--no-cli-pager]
[--cli-auto-prompt]
[--no-cli-auto-prompt]

Options

--transcription-job-name (string)

A unique name, chosen by you, for your 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 OutputKey parameter.

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 ConflictException error.

--language-code (string)

The language code that represents the language spoken in the input media file.

If you’re unsure of the language spoken in your media file, consider using IdentifyLanguage or IdentifyMultipleLanguages to enable automatic language identification.

Note that you must include one of LanguageCode , IdentifyLanguage , or IdentifyMultipleLanguages in your request. If you include more than one of these parameters, your transcription job fails.

For a list of supported languages and their associated language codes, refer to the Supported languages table.

Note

To transcribe speech in Modern Standard Arabic (ar-SA ), your media file must be encoded at a sample rate of 16,000 Hz or higher.

Possible values:

  • af-ZA

  • ar-AE

  • ar-SA

  • da-DK

  • de-CH

  • de-DE

  • en-AB

  • en-AU

  • en-GB

  • en-IE

  • en-IN

  • en-US

  • en-WL

  • es-ES

  • es-US

  • fa-IR

  • fr-CA

  • fr-FR

  • he-IL

  • hi-IN

  • id-ID

  • it-IT

  • ja-JP

  • ko-KR

  • ms-MY

  • nl-NL

  • pt-BR

  • pt-PT

  • ru-RU

  • ta-IN

  • te-IN

  • tr-TR

  • zh-CN

  • zh-TW

  • th-TH

  • en-ZA

  • en-NZ

--media-sample-rate-hertz (integer)

The sample rate, in hertz, of the audio track in your input media file.

If you don’t specify the media sample rate, Amazon Transcribe determines it for you. If you specify the sample rate, it must match the rate detected by Amazon Transcribe. If there’s a mismatch between the value that you specify and the value detected, your job fails. In most cases, you can omit MediaSampleRateHertz and let Amazon Transcribe determine the sample rate.

--media-format (string)

Specify the format of your input media file.

Possible values:

  • mp3

  • mp4

  • wav

  • flac

  • ogg

  • amr

  • webm

--media (structure)

Describes the Amazon S3 location of the media file you want to use in your request.

MediaFileUri -> (string)

The Amazon S3 location of the media file you want to transcribe. For example:

  • s3://DOC-EXAMPLE-BUCKET/my-media-file.flac

  • s3://DOC-EXAMPLE-BUCKET/media-files/my-media-file.flac

Note that the Amazon S3 bucket that contains your input media must be located in the same Amazon Web Services Region where you’re making your transcription request.

RedactedMediaFileUri -> (string)

The Amazon S3 location of the media file you want to redact. For example:

  • s3://DOC-EXAMPLE-BUCKET/my-media-file.flac

  • s3://DOC-EXAMPLE-BUCKET/media-files/my-media-file.flac

Note that the Amazon S3 bucket that contains your input media must be located in the same Amazon Web Services Region where you’re making your transcription request.

Warning

RedactedMediaFileUri produces a redacted audio file in addition to a redacted transcript. It is only supported for Call Analytics (StartCallAnalyticsJob ) transcription requests.

Shorthand Syntax:

MediaFileUri=string,RedactedMediaFileUri=string

JSON Syntax:

{
  "MediaFileUri": "string",
  "RedactedMediaFileUri": "string"
}

--output-bucket-name (string)

The name of the Amazon S3 bucket where you want your transcription output stored. Do not include the S3:// prefix of the specified bucket.

If you want your output to go to a sub-folder of this bucket, specify it using the OutputKey parameter; OutputBucketName only accepts the name of a bucket.

For example, if you want your output stored in S3://DOC-EXAMPLE-BUCKET , set OutputBucketName to DOC-EXAMPLE-BUCKET . However, if you want your output stored in S3://DOC-EXAMPLE-BUCKET/test-files/ , set OutputBucketName to DOC-EXAMPLE-BUCKET and OutputKey to test-files/ .

Note that Amazon Transcribe must have permission to use the specified location. You can change Amazon S3 permissions using the Amazon Web Services Management Console . See also Permissions Required for IAM User Roles .

If you don’t specify OutputBucketName , your transcript is placed in a service-managed Amazon S3 bucket and you are provided with a URI to access your transcript.

--output-key (string)

Use in combination with OutputBucketName 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 transcription job (TranscriptionJobName ).

Here are some examples of how you can use OutputKey :

  • If you specify ‘DOC-EXAMPLE-BUCKET’ as the OutputBucketName and ‘my-transcript.json’ as the OutputKey , your transcription output path is s3://DOC-EXAMPLE-BUCKET/my-transcript.json .

  • If you specify ‘my-first-transcription’ as the TranscriptionJobName , ‘DOC-EXAMPLE-BUCKET’ as the OutputBucketName , and ‘my-transcript’ as the OutputKey , your transcription output path is s3://DOC-EXAMPLE-BUCKET/my-transcript/my-first-transcription.json .

  • If you specify ‘DOC-EXAMPLE-BUCKET’ as the OutputBucketName and ‘test-files/my-transcript.json’ as the OutputKey , your transcription output path is s3://DOC-EXAMPLE-BUCKET/test-files/my-transcript.json .

  • If you specify ‘my-first-transcription’ as the TranscriptionJobName , ‘DOC-EXAMPLE-BUCKET’ as the OutputBucketName , and ‘test-files/my-transcript’ as the OutputKey , your transcription output path is s3://DOC-EXAMPLE-BUCKET/test-files/my-transcript/my-first-transcription.json .

If you specify the name of an Amazon S3 bucket sub-folder that doesn’t exist, one is created for you.

--output-encryption-kms-key-id (string)

The KMS key you want to use to encrypt your transcription output.

If using a key located in the current Amazon Web Services account, you can specify your KMS key in one of four ways:

  • Use the KMS key ID itself. For example, 1234abcd-12ab-34cd-56ef-1234567890ab .

  • Use an alias for the KMS key ID. For example, alias/ExampleAlias .

  • Use the Amazon Resource Name (ARN) for the KMS key ID. For example, arn:aws:kms:region:account-ID:key/1234abcd-12ab-34cd-56ef-1234567890ab .

  • Use the ARN for the KMS key alias. For example, arn:aws:kms:region:account-ID:alias/ExampleAlias .

If using a key located in a different Amazon Web Services account than the current Amazon Web Services account, you can specify your KMS key in one of two ways:

  • Use the ARN for the KMS key ID. For example, arn:aws:kms:region:account-ID:key/1234abcd-12ab-34cd-56ef-1234567890ab .

  • Use the ARN for the KMS key alias. For example, arn:aws:kms:region:account-ID:alias/ExampleAlias .

If you don’t specify an encryption key, your output is encrypted with the default Amazon S3 key (SSE-S3).

If you specify a KMS key to encrypt your output, you must also specify an output location using the OutputLocation parameter.

Note that the user making the request must have permission to use the specified KMS key.

--kms-encryption-context (map)

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 KMS encryption context and Asymmetric keys in KMS .

key -> (string)

value -> (string)

Shorthand Syntax:

KeyName1=string,KeyName2=string

JSON Syntax:

{"string": "string"
  ...}

--settings (structure)

Specify additional optional settings in your request, including channel identification, alternative transcriptions, speaker partitioning. You can use that to apply custom vocabularies and vocabulary filters.

If you want to include a custom vocabulary or a custom vocabulary filter (or both) with your request but do not want to use automatic language identification, use Settings with the VocabularyName or VocabularyFilterName (or both) sub-parameter.

If you’re using automatic language identification with your request and want to include a custom language model, a custom vocabulary, or a custom vocabulary filter, use instead the parameter with the LanguageModelName , VocabularyName or VocabularyFilterName sub-parameters.

VocabularyName -> (string)

The name of the custom vocabulary you want to use in your transcription job request. This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account.

ShowSpeakerLabels -> (boolean)

Enables speaker partitioning (diarization) in your transcription output. Speaker partitioning labels the speech from individual speakers in your media file.

If you enable ShowSpeakerLabels in your request, you must also include MaxSpeakerLabels .

You can’t include both ShowSpeakerLabels and ChannelIdentification in the same request. Including both parameters returns a BadRequestException .

For more information, see Partitioning speakers (diarization) .

MaxSpeakerLabels -> (integer)

Specify the maximum number of speakers you want to partition in your media.

Note that if your media contains more speakers than the specified number, multiple speakers are treated as a single speaker.

If you specify the MaxSpeakerLabels field, you must set the ShowSpeakerLabels field to true.

ChannelIdentification -> (boolean)

Enables channel identification in multi-channel audio.

Channel identification transcribes the audio on each channel independently, then appends the output for each channel into one transcript.

You can’t include both ShowSpeakerLabels and ChannelIdentification in the same request. Including both parameters returns a BadRequestException .

For more information, see Transcribing multi-channel audio .

ShowAlternatives -> (boolean)

To include alternative transcriptions within your transcription output, include ShowAlternatives in your transcription request.

If you have multi-channel audio and do not enable channel identification, your audio is transcribed in a continuous manner and your transcript does not separate the speech by channel.

If you include ShowAlternatives , you must also include MaxAlternatives , which is the maximum number of alternative transcriptions you want Amazon Transcribe to generate.

For more information, see Alternative transcriptions .

MaxAlternatives -> (integer)

Indicate the maximum number of alternative transcriptions you want Amazon Transcribe to include in your transcript.

If you select a number greater than the number of alternative transcriptions generated by Amazon Transcribe, only the actual number of alternative transcriptions are included.

If you include MaxAlternatives in your request, you must also include ShowAlternatives with a value of true .

For more information, see Alternative transcriptions .

VocabularyFilterName -> (string)

The name of the custom vocabulary filter you want to use in your transcription job request. This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account.

Note that if you include VocabularyFilterName in your request, you must also include VocabularyFilterMethod .

VocabularyFilterMethod -> (string)

Specify how you want your custom vocabulary filter applied to your transcript.

To replace words with *** , choose mask .

To delete words, choose remove .

To flag words without changing them, choose tag .

Shorthand Syntax:

VocabularyName=string,ShowSpeakerLabels=boolean,MaxSpeakerLabels=integer,ChannelIdentification=boolean,ShowAlternatives=boolean,MaxAlternatives=integer,VocabularyFilterName=string,VocabularyFilterMethod=string

JSON Syntax:

{
  "VocabularyName": "string",
  "ShowSpeakerLabels": true|false,
  "MaxSpeakerLabels": integer,
  "ChannelIdentification": true|false,
  "ShowAlternatives": true|false,
  "MaxAlternatives": integer,
  "VocabularyFilterName": "string",
  "VocabularyFilterMethod": "remove"|"mask"|"tag"
}

--model-settings (structure)

Specify the custom language model you want to include with your transcription job. If you include ModelSettings in your request, you must include the LanguageModelName sub-parameter.

For more information, see Custom language models .

LanguageModelName -> (string)

The name of the custom language model you want to use when processing your transcription job. Note that custom language model names are case sensitive.

The language of the specified custom language model must match the language code that you specify in your transcription request. If the languages don’t match, the custom language model isn’t applied. There are no errors or warnings associated with a language mismatch.

Shorthand Syntax:

LanguageModelName=string

JSON Syntax:

{
  "LanguageModelName": "string"
}

--job-execution-settings (structure)

Makes it possible to control how your transcription job is processed. Currently, the only JobExecutionSettings modification you can choose is enabling job queueing using the AllowDeferredExecution sub-parameter.

If you include JobExecutionSettings in your request, you must also include the sub-parameters: AllowDeferredExecution and DataAccessRoleArn .

AllowDeferredExecution -> (boolean)

Makes it possible to enable job queuing when your concurrent request limit is exceeded. When AllowDeferredExecution is set to true , transcription job requests are placed in a queue until the number of jobs falls below the concurrent request limit. If AllowDeferredExecution is set to false and the number of transcription job requests exceed the concurrent request limit, you get a LimitExceededException error.

Note that job queuing is enabled by default for Call Analytics jobs.

If you include AllowDeferredExecution in your request, you must also include DataAccessRoleArn .

DataAccessRoleArn -> (string)

The Amazon Resource Name (ARN) of an IAM role that has permissions to access the Amazon S3 bucket that contains your input files. If the role that you specify doesn’t have the appropriate permissions to access the specified Amazon S3 location, your request fails.

IAM role ARNs have the format arn:partition:iam::account:role/role-name-with-path . For example: arn:aws:iam::111122223333:role/Admin . For more information, see IAM ARNs .

Note that if you include DataAccessRoleArn in your request, you must also include AllowDeferredExecution .

Shorthand Syntax:

AllowDeferredExecution=boolean,DataAccessRoleArn=string

JSON Syntax:

{
  "AllowDeferredExecution": true|false,
  "DataAccessRoleArn": "string"
}

--content-redaction (structure)

Makes it possible to redact or flag specified personally identifiable information (PII) in your transcript. If you use ContentRedaction , you must also include the sub-parameters: PiiEntityTypes , RedactionOutput , and RedactionType .

RedactionType -> (string)

Specify the category of information you want to redact; PII (personally identifiable information) is the only valid value. You can use PiiEntityTypes to choose which types of PII you want to redact.

RedactionOutput -> (string)

Specify if you want only a redacted transcript, or if you want a redacted and an unredacted transcript.

When you choose redacted Amazon Transcribe creates only a redacted transcript.

When you choose redacted_and_unredacted Amazon Transcribe creates a redacted and an unredacted transcript (as two separate files).

PiiEntityTypes -> (list)

Specify which types of personally identifiable information (PII) you want to redact in your transcript. You can include as many types as you’d like, or you can select ALL .

(string)

Shorthand Syntax:

RedactionType=string,RedactionOutput=string,PiiEntityTypes=string,string

JSON Syntax:

{
  "RedactionType": "PII",
  "RedactionOutput": "redacted"|"redacted_and_unredacted",
  "PiiEntityTypes": ["BANK_ACCOUNT_NUMBER"|"BANK_ROUTING"|"CREDIT_DEBIT_NUMBER"|"CREDIT_DEBIT_CVV"|"CREDIT_DEBIT_EXPIRY"|"PIN"|"EMAIL"|"ADDRESS"|"NAME"|"PHONE"|"SSN"|"ALL", ...]
}

--identify-language | --no-identify-language (boolean)

Enables automatic language identification in your transcription job request. Use this parameter if your media file contains only one language. If your media contains multiple languages, use IdentifyMultipleLanguages instead.

If you include IdentifyLanguage , you can optionally include a list of language codes, using LanguageOptions , that you think may be present in your media file. Including LanguageOptions restricts IdentifyLanguage to only the language options that you specify, which can improve transcription accuracy.

If you want to apply a custom language model, a custom vocabulary, or a custom vocabulary filter to your automatic language identification request, include LanguageIdSettings with the relevant sub-parameters (VocabularyName , LanguageModelName , and VocabularyFilterName ). If you include LanguageIdSettings , also include LanguageOptions .

Note that you must include one of LanguageCode , IdentifyLanguage , or IdentifyMultipleLanguages in your request. If you include more than one of these parameters, your transcription job fails.

--identify-multiple-languages | --no-identify-multiple-languages (boolean)

Enables automatic multi-language identification in your transcription job request. Use this parameter if your media file contains more than one language. If your media contains only one language, use IdentifyLanguage instead.

If you include IdentifyMultipleLanguages , you can optionally include a list of language codes, using LanguageOptions , that you think may be present in your media file. Including LanguageOptions restricts IdentifyLanguage to only the language options that you specify, which can improve transcription accuracy.

If you want to apply a custom vocabulary or a custom vocabulary filter to your automatic language identification request, include LanguageIdSettings with the relevant sub-parameters (VocabularyName and VocabularyFilterName ). If you include LanguageIdSettings , also include LanguageOptions .

Note that you must include one of LanguageCode , IdentifyLanguage , or IdentifyMultipleLanguages in your request. If you include more than one of these parameters, your transcription job fails.

--language-options (list)

You can specify two or more language codes that represent the languages you think may be present in your media. Including more than five is not recommended. If you’re unsure what languages are present, do not include this parameter.

If you include LanguageOptions in your request, you must also include IdentifyLanguage .

For more information, refer to Supported languages .

To transcribe speech in Modern Standard Arabic (ar-SA ), your media file must be encoded at a sample rate of 16,000 Hz or higher.

(string)

Syntax:

"string" "string" ...

Where valid values are:
  af-ZA
  ar-AE
  ar-SA
  da-DK
  de-CH
  de-DE
  en-AB
  en-AU
  en-GB
  en-IE
  en-IN
  en-US
  en-WL
  es-ES
  es-US
  fa-IR
  fr-CA
  fr-FR
  he-IL
  hi-IN
  id-ID
  it-IT
  ja-JP
  ko-KR
  ms-MY
  nl-NL
  pt-BR
  pt-PT
  ru-RU
  ta-IN
  te-IN
  tr-TR
  zh-CN
  zh-TW
  th-TH
  en-ZA
  en-NZ

--subtitles (structure)

Produces subtitle files for your input media. You can specify WebVTT (.vtt) and SubRip (.srt) formats.

Formats -> (list)

Specify the output format for your subtitle file; if you select both WebVTT (vtt ) and SubRip (srt ) formats, two output files are generated.

(string)

OutputStartIndex -> (integer)

Specify the starting value that is assigned to the first subtitle segment.

The default start index for Amazon Transcribe is 0 , which differs from the more widely used standard of 1 . If you’re uncertain which value to use, we recommend choosing 1 , as this may improve compatibility with other services.

Shorthand Syntax:

Formats=string,string,OutputStartIndex=integer

JSON Syntax:

{
  "Formats": ["vtt"|"srt", ...],
  "OutputStartIndex": integer
}

--tags (list)

Adds one or more custom tags, each in the form of a key:value pair, to a new transcription job at the time you start this new job.

To learn more about using tags with Amazon Transcribe, refer to Tagging resources .

(structure)

Adds metadata, in the form of a key:value pair, to the specified resource.

For example, you could add the tag Department:Sales to a resource to indicate that it pertains to your organization’s sales department. You can also use tags for tag-based access control.

To learn more about tagging, see Tagging resources .

Key -> (string)

The first part of a key:value pair that forms a tag associated with a given resource. For example, in the tag Department:Sales , the key is ‘Department’.

Value -> (string)

The second part of a key:value pair that forms a tag associated with a given resource. For example, in the tag Department:Sales , the value is ‘Sales’.

Note that you can set the value of a tag to an empty string, but you can’t set the value of a tag to null. Omitting the tag value is the same as using an empty string.

Shorthand Syntax:

Key=string,Value=string ...

JSON Syntax:

[
  {
    "Key": "string",
    "Value": "string"
  }
  ...
]

--language-id-settings (map)

If using automatic language identification in your request and you want to apply a custom language model, a custom vocabulary, or a custom vocabulary filter, include LanguageIdSettings with the relevant sub-parameters (VocabularyName , LanguageModelName , and VocabularyFilterName ). Note that multi-language identification (IdentifyMultipleLanguages ) doesn’t support custom language models.

LanguageIdSettings supports two to five language codes. Each language code you include can have an associated custom language model, custom vocabulary, and custom vocabulary filter. The language codes that you specify must match the languages of the associated custom language models, custom vocabularies, and custom vocabulary filters.

It’s recommended that you include LanguageOptions when using LanguageIdSettings to ensure that the correct language dialect is identified. For example, if you specify a custom vocabulary that is in en-US but Amazon Transcribe determines that the language spoken in your media is en-AU , your custom vocabulary is not applied to your transcription. If you include LanguageOptions and include en-US as the only English language dialect, your custom vocabulary is applied to your transcription.

If you want to include a custom language model with your request but do not want to use automatic language identification, use instead the parameter with the LanguageModelName sub-parameter. If you want to include a custom vocabulary or a custom vocabulary filter (or both) with your request but do not want to use automatic language identification, use instead the parameter with the VocabularyName or VocabularyFilterName (or both) sub-parameter.

key -> (string)

value -> (structure)

If using automatic language identification in your request and you want to apply a custom language model, a custom vocabulary, or a custom vocabulary filter, include LanguageIdSettings with the relevant sub-parameters (VocabularyName , LanguageModelName , and VocabularyFilterName ). Note that multi-language identification (IdentifyMultipleLanguages ) doesn’t support custom language models.

LanguageIdSettings supports two to five language codes. Each language code you include can have an associated custom language model, custom vocabulary, and custom vocabulary filter. The language codes that you specify must match the languages of the associated custom language models, custom vocabularies, and custom vocabulary filters.

It’s recommended that you include LanguageOptions when using LanguageIdSettings to ensure that the correct language dialect is identified. For example, if you specify a custom vocabulary that is in en-US but Amazon Transcribe determines that the language spoken in your media is en-AU , your custom vocabulary is not applied to your transcription. If you include LanguageOptions and include en-US as the only English language dialect, your custom vocabulary is applied to your transcription.

If you want to include a custom language model with your request but do not want to use automatic language identification, use instead the parameter with the LanguageModelName sub-parameter. If you want to include a custom vocabulary or a custom vocabulary filter (or both) with your request but do not want to use automatic language identification, use instead the parameter with the VocabularyName or VocabularyFilterName (or both) sub-parameter.

VocabularyName -> (string)

The name of the custom vocabulary you want to use when processing your transcription job. Custom vocabulary names are case sensitive.

The language of the specified custom vocabulary must match the language code that you specify in your transcription request. If the languages don’t match, the custom vocabulary isn’t applied. There are no errors or warnings associated with a language mismatch.

VocabularyFilterName -> (string)

The name of the custom vocabulary filter you want to use when processing your transcription job. Custom vocabulary filter names are case sensitive.

The language of the specified custom vocabulary filter must match the language code that you specify in your transcription request. If the languages don’t match, the custom vocabulary filter isn’t applied. There are no errors or warnings associated with a language mismatch.

Note that if you include VocabularyFilterName in your request, you must also include VocabularyFilterMethod .

LanguageModelName -> (string)

The name of the custom language model you want to use when processing your transcription job. Note that custom language model names are case sensitive.

The language of the specified custom language model must match the language code that you specify in your transcription request. If the languages don’t match, the custom language model isn’t applied. There are no errors or warnings associated with a language mismatch.

Shorthand Syntax:

  KeyName1=VocabularyName=string,VocabularyFilterName=string,LanguageModelName=string,KeyName2=VocabularyName=string,VocabularyFilterName=string,LanguageModelName=string

Where valid key names are:
  af-ZA
  ar-AE
  ar-SA
  da-DK
  de-CH
  de-DE
  en-AB
  en-AU
  en-GB
  en-IE
  en-IN
  en-US
  en-WL
  es-ES
  es-US
  fa-IR
  fr-CA
  fr-FR
  he-IL
  hi-IN
  id-ID
  it-IT
  ja-JP
  ko-KR
  ms-MY
  nl-NL
  pt-BR
  pt-PT
  ru-RU
  ta-IN
  te-IN
  tr-TR
  zh-CN
  zh-TW
  th-TH
  en-ZA
  en-NZ

JSON Syntax:

{"af-ZA"|"ar-AE"|"ar-SA"|"da-DK"|"de-CH"|"de-DE"|"en-AB"|"en-AU"|"en-GB"|"en-IE"|"en-IN"|"en-US"|"en-WL"|"es-ES"|"es-US"|"fa-IR"|"fr-CA"|"fr-FR"|"he-IL"|"hi-IN"|"id-ID"|"it-IT"|"ja-JP"|"ko-KR"|"ms-MY"|"nl-NL"|"pt-BR"|"pt-PT"|"ru-RU"|"ta-IN"|"te-IN"|"tr-TR"|"zh-CN"|"zh-TW"|"th-TH"|"en-ZA"|"en-NZ": {
      "VocabularyName": "string",
      "VocabularyFilterName": "string",
      "LanguageModelName": "string"
    }
  ...}

--cli-input-json | --cli-input-yaml (string) Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command. The generated JSON skeleton is not stable between versions of the AWS CLI and there are no backwards compatibility guarantees in the JSON skeleton generated.

Global Options

--debug (boolean)

Turn on debug logging.

--endpoint-url (string)

Override command’s default URL with the given URL.

--no-verify-ssl (boolean)

By default, the AWS CLI uses SSL when communicating with AWS services. For each SSL connection, the AWS CLI will verify SSL certificates. This option overrides the default behavior of verifying SSL certificates.

--no-paginate (boolean)

Disable automatic pagination.

--output (string)

The formatting style for command output.

  • json

  • text

  • table

  • yaml

  • yaml-stream

--query (string)

A JMESPath query to use in filtering the response data.

--profile (string)

Use a specific profile from your credential file.

--region (string)

The region to use. Overrides config/env settings.

--version (string)

Display the version of this tool.

--color (string)

Turn on/off color output.

  • on

  • off

  • auto

--no-sign-request (boolean)

Do not sign requests. Credentials will not be loaded if this argument is provided.

--ca-bundle (string)

The CA certificate bundle to use when verifying SSL certificates. Overrides config/env settings.

--cli-read-timeout (int)

The maximum socket read time in seconds. If the value is set to 0, the socket read will be blocking and not timeout. The default value is 60 seconds.

--cli-connect-timeout (int)

The maximum socket connect time in seconds. If the value is set to 0, the socket connect will be blocking and not timeout. The default value is 60 seconds.

--cli-binary-format (string)

The formatting style to be used for binary blobs. The default format is base64. The base64 format expects binary blobs to be provided as a base64 encoded string. The raw-in-base64-out format preserves compatibility with AWS CLI V1 behavior and binary values must be passed literally. When providing contents from a file that map to a binary blob fileb:// will always be treated as binary and use the file contents directly regardless of the cli-binary-format setting. When using file:// the file contents will need to properly formatted for the configured cli-binary-format.

  • base64

  • raw-in-base64-out

--no-cli-pager (boolean)

Disable cli pager for output.

--cli-auto-prompt (boolean)

Automatically prompt for CLI input parameters.

--no-cli-auto-prompt (boolean)

Disable automatically prompt for CLI input parameters.

Examples

Note

To use the following examples, you must have the AWS CLI installed and configured. See the Getting started guide in the AWS CLI User Guide for more information.

Unless otherwise stated, all examples have unix-like quotation rules. These examples will need to be adapted to your terminal’s quoting rules. See Using quotation marks with strings in the AWS CLI User Guide .

Example 1: To transcribe an audio file

The following start-transcription-job example transcribes your audio file.

aws transcribe start-transcription-job \
    --cli-input-json file://myfile.json

Contents of myfile.json:

{
    "TranscriptionJobName": "cli-simple-transcription-job",
    "LanguageCode": "the-language-of-your-transcription-job",
    "Media": {
        "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
    }
}

For more information, see Getting Started (AWS Command Line Interface) in the Amazon Transcribe Developer Guide.

Example 2: To transcribe a multi-channel audio file

The following start-transcription-job example transcribes your multi-channel audio file.

aws transcribe start-transcription-job \
    --cli-input-json file://mysecondfile.json

Contents of mysecondfile.json:

{
    "TranscriptionJobName": "cli-channelid-job",
    "LanguageCode": "the-language-of-your-transcription-job",
    "Media": {
        "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
    },
    "Settings":{
        "ChannelIdentification":true
    }
}

Output:

{
    "TranscriptionJob": {
        "TranscriptionJobName": "cli-channelid-job",
        "TranscriptionJobStatus": "IN_PROGRESS",
        "LanguageCode": "the-language-of-your-transcription-job",
        "Media": {
            "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
        },
        "StartTime": "2020-09-17T16:07:56.817000+00:00",
        "CreationTime": "2020-09-17T16:07:56.784000+00:00",
        "Settings": {
            "ChannelIdentification": true
        }
    }
}

For more information, see Transcribing Multi-Channel Audio in the Amazon Transcribe Developer Guide.

Example 3: To transcribe an audio file and identify the different speakers

The following start-transcription-job example transcribes your audio file and identifies the speakers in the transcription output.

aws transcribe start-transcription-job \
    --cli-input-json file://mythirdfile.json

Contents of mythirdfile.json:

{
    "TranscriptionJobName": "cli-speakerid-job",
    "LanguageCode": "the-language-of-your-transcription-job",
    "Media": {
        "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
    },
    "Settings":{
    "ShowSpeakerLabels": true,
    "MaxSpeakerLabels": 2
    }
}

Output:

{
    "TranscriptionJob": {
        "TranscriptionJobName": "cli-speakerid-job",
        "TranscriptionJobStatus": "IN_PROGRESS",
        "LanguageCode": "the-language-of-your-transcription-job",
        "Media": {
            "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
        },
        "StartTime": "2020-09-17T16:22:59.696000+00:00",
        "CreationTime": "2020-09-17T16:22:59.676000+00:00",
        "Settings": {
            "ShowSpeakerLabels": true,
            "MaxSpeakerLabels": 2
        }
    }
}

For more information, see Identifying Speakers in the Amazon Transcribe Developer Guide.

Example 4: To transcribe an audio file and mask any unwanted words in the transcription output

The following start-transcription-job example transcribes your audio file and uses a vocabulary filter you’ve previously created to mask any unwanted words.

aws transcribe start-transcription-job \
    --cli-input-json file://myfourthfile.json

Contents of myfourthfile.json:

{
    "TranscriptionJobName": "cli-filter-mask-job",
    "LanguageCode": "the-language-of-your-transcription-job",
    "Media": {
          "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
    },
    "Settings":{
        "VocabularyFilterName": "your-vocabulary-filter",
        "VocabularyFilterMethod": "mask"
    }
}

Output:

{
    "TranscriptionJob": {
        "TranscriptionJobName": "cli-filter-mask-job",
        "TranscriptionJobStatus": "IN_PROGRESS",
        "LanguageCode": "the-language-of-your-transcription-job",
        "Media": {
            "MediaFileUri": "s3://Amazon-S3-Prefix/your-media-file.file-extension"
        },
        "StartTime": "2020-09-18T16:36:18.568000+00:00",
        "CreationTime": "2020-09-18T16:36:18.547000+00:00",
        "Settings": {
            "VocabularyFilterName": "your-vocabulary-filter",
            "VocabularyFilterMethod": "mask"
        }
    }
}

For more information, see Filtering Transcriptions in the Amazon Transcribe Developer Guide.

Example 5: To transcribe an audio file and remove any unwanted words in the transcription output

The following start-transcription-job example transcribes your audio file and uses a vocabulary filter you’ve previously created to mask any unwanted words.

aws transcribe start-transcription-job \
    --cli-input-json file://myfifthfile.json

Contents of myfifthfile.json:

{
    "TranscriptionJobName": "cli-filter-remove-job",
    "LanguageCode": "the-language-of-your-transcription-job",
    "Media": {
        "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
    },
    "Settings":{
        "VocabularyFilterName": "your-vocabulary-filter",
        "VocabularyFilterMethod": "remove"
    }
}

Output:

{
    "TranscriptionJob": {
        "TranscriptionJobName": "cli-filter-remove-job",
        "TranscriptionJobStatus": "IN_PROGRESS",
        "LanguageCode": "the-language-of-your-transcription-job",
        "Media": {
            "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
        },
        "StartTime": "2020-09-18T16:36:18.568000+00:00",
        "CreationTime": "2020-09-18T16:36:18.547000+00:00",
        "Settings": {
            "VocabularyFilterName": "your-vocabulary-filter",
            "VocabularyFilterMethod": "remove"
        }
    }
}

For more information, see Filtering Transcriptions in the Amazon Transcribe Developer Guide.

Example 6: To transcribe an audio file with increased accuracy using a custom vocabulary

The following start-transcription-job example transcribes your audio file and uses a vocabulary filter you’ve previously created to mask any unwanted words.

aws transcribe start-transcription-job \
    --cli-input-json file://mysixthfile.json

Contents of mysixthfile.json:

{
    "TranscriptionJobName": "cli-vocab-job",
    "LanguageCode": "the-language-of-your-transcription-job",
    "Media": {
        "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
    },
    "Settings":{
        "VocabularyName": "your-vocabulary"
    }
}

Output:

{
    "TranscriptionJob": {
        "TranscriptionJobName": "cli-vocab-job",
        "TranscriptionJobStatus": "IN_PROGRESS",
        "LanguageCode": "the-language-of-your-transcription-job",
        "Media": {
            "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
        },
        "StartTime": "2020-09-18T16:36:18.568000+00:00",
        "CreationTime": "2020-09-18T16:36:18.547000+00:00",
        "Settings": {
            "VocabularyName": "your-vocabulary"
        }
    }
}

For more information, see Filtering Transcriptions in the Amazon Transcribe Developer Guide.

Example 7: To identify the language of an audio file and transcribe it

The following start-transcription-job example transcribes your audio file and uses a vocabulary filter you’ve previously created to mask any unwanted words.

aws transcribe start-transcription-job \
    --cli-input-json file://myseventhfile.json

Contents of myseventhfile.json:

{
    "TranscriptionJobName": "cli-identify-language-transcription-job",
    "IdentifyLanguage": true,
    "Media": {
        "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
    }
}

Output:

{
    "TranscriptionJob": {
        "TranscriptionJobName": "cli-identify-language-transcription-job",
        "TranscriptionJobStatus": "IN_PROGRESS",
        "Media": {
            "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
        },
        "StartTime": "2020-09-18T22:27:23.970000+00:00",
        "CreationTime": "2020-09-18T22:27:23.948000+00:00",
        "IdentifyLanguage": true
    }
}

For more information, see Identifying the Language in the Amazon Transcribe Developer Guide.

Example 8: To transcribe an audio file with personally identifiable information redacted

The following start-transcription-job example transcribes your audio file and redacts any personally identifiable information in the transcription output.

aws transcribe start-transcription-job \
    --cli-input-json file://myeighthfile.json

Contents of myeigthfile.json:

{
    "TranscriptionJobName": "cli-redaction-job",
    "LanguageCode": "language-code",
    "Media": {
        "MediaFileUri": "s3://Amazon-S3-Prefix/your-media-file.file-extension"
    },
    "ContentRedaction": {
        "RedactionOutput":"redacted",
        "RedactionType":"PII"
    }
}

Output:

{
    "TranscriptionJob": {
        "TranscriptionJobName": "cli-redaction-job",
        "TranscriptionJobStatus": "IN_PROGRESS",
        "LanguageCode": "language-code",
        "Media": {
            "MediaFileUri": "s3://Amazon-S3-Prefix/your-media-file.file-extension"
        },
        "StartTime": "2020-09-25T23:49:13.195000+00:00",
        "CreationTime": "2020-09-25T23:49:13.176000+00:00",
        "ContentRedaction": {
            "RedactionType": "PII",
            "RedactionOutput": "redacted"
        }
    }
}

For more information, see Automatic Content Redaction in the Amazon Transcribe Developer Guide.

Example 9: To generate a transcript with personally identifiable information (PII) redacted and an unredacted transcript

The following start-transcription-job example generates two transcrptions of your audio file, one with the personally identifiable information redacted, and the other without any redactions.

aws transcribe start-transcription-job \
    --cli-input-json file://myninthfile.json

Contents of myninthfile.json:

{
    "TranscriptionJobName": "cli-redaction-job-with-unredacted-transcript",
    "LanguageCode": "language-code",
    "Media": {
          "MediaFileUri": "s3://Amazon-S3-Prefix/your-media-file.file-extension"
        },
    "ContentRedaction": {
        "RedactionOutput":"redacted_and_unredacted",
        "RedactionType":"PII"
    }
}

Output:

{
    "TranscriptionJob": {
        "TranscriptionJobName": "cli-redaction-job-with-unredacted-transcript",
        "TranscriptionJobStatus": "IN_PROGRESS",
        "LanguageCode": "language-code",
        "Media": {
            "MediaFileUri": "s3://Amazon-S3-Prefix/your-media-file.file-extension"
        },
        "StartTime": "2020-09-25T23:59:47.677000+00:00",
        "CreationTime": "2020-09-25T23:59:47.653000+00:00",
        "ContentRedaction": {
            "RedactionType": "PII",
            "RedactionOutput": "redacted_and_unredacted"
        }
    }
}

For more information, see Automatic Content Redaction in the Amazon Transcribe Developer Guide.

Example 10: To use a custom language model you’ve previously created to transcribe an audio file.

The following start-transcription-job example transcribes your audio file with a custom language model you’ve previously created.

aws transcribe start-transcription-job \
    --cli-input-json file://mytenthfile.json

Contents of mytenthfile.json:

{
    "TranscriptionJobName": "cli-clm-2-job-1",
    "LanguageCode": "language-code",
    "Media": {
        "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.file-extension"
    },
    "ModelSettings": {
        "LanguageModelName":"cli-clm-2"
    }
}

Output:

{
    "TranscriptionJob": {
        "TranscriptionJobName": "cli-clm-2-job-1",
        "TranscriptionJobStatus": "IN_PROGRESS",
        "LanguageCode": "language-code",
        "Media": {
            "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.file-extension"
        },
        "StartTime": "2020-09-28T17:56:01.835000+00:00",
        "CreationTime": "2020-09-28T17:56:01.801000+00:00",
        "ModelSettings": {
            "LanguageModelName": "cli-clm-2"
        }
    }
}

For more information, see Improving Domain-Specific Transcription Accuracy with Custom Language Models in the Amazon Transcribe Developer Guide.

Output

TranscriptionJob -> (structure)

Provides detailed information about the current transcription job, including job status and, if applicable, failure reason.

TranscriptionJobName -> (string)

The name of the transcription job. Job names are case sensitive and must be unique within an Amazon Web Services account.

TranscriptionJobStatus -> (string)

Provides the status of the specified transcription job.

If the status is COMPLETED , the job is finished and you can find the results at the location specified in TranscriptFileUri (or RedactedTranscriptFileUri , if you requested transcript redaction). If the status is FAILED , FailureReason provides details on why your transcription job failed.

LanguageCode -> (string)

The language code used to create your transcription job. This parameter is used with single-language identification. For multi-language identification requests, refer to the plural version of this parameter, LanguageCodes .

MediaSampleRateHertz -> (integer)

The sample rate, in hertz, of the audio track in your input media file.

MediaFormat -> (string)

The format of the input media file.

Media -> (structure)

Provides the Amazon S3 location of the media file you used in your request.

MediaFileUri -> (string)

The Amazon S3 location of the media file you want to transcribe. For example:

  • s3://DOC-EXAMPLE-BUCKET/my-media-file.flac

  • s3://DOC-EXAMPLE-BUCKET/media-files/my-media-file.flac

Note that the Amazon S3 bucket that contains your input media must be located in the same Amazon Web Services Region where you’re making your transcription request.

RedactedMediaFileUri -> (string)

The Amazon S3 location of the media file you want to redact. For example:

  • s3://DOC-EXAMPLE-BUCKET/my-media-file.flac

  • s3://DOC-EXAMPLE-BUCKET/media-files/my-media-file.flac

Note that the Amazon S3 bucket that contains your input media must be located in the same Amazon Web Services Region where you’re making your transcription request.

Warning

RedactedMediaFileUri produces a redacted audio file in addition to a redacted transcript. It is only supported for Call Analytics (StartCallAnalyticsJob ) transcription requests.

Transcript -> (structure)

Provides you with the Amazon S3 URI you can use to access your transcript.

TranscriptFileUri -> (string)

The Amazon S3 location of your transcript. You can use this URI to access or download your transcript.

If you included OutputBucketName in your transcription job request, this is the URI of that bucket. If you also included OutputKey in your request, your output is located in the path you specified in your request.

If you didn’t include OutputBucketName in your transcription job request, your transcript is stored in a service-managed bucket, and TranscriptFileUri provides you with a temporary URI you can use for secure access to your transcript.

Note

Temporary URIs for service-managed Amazon S3 buckets are only valid for 15 minutes. If you get an AccesDenied error, you can get a new temporary URI by running a GetTranscriptionJob or ListTranscriptionJob request.

RedactedTranscriptFileUri -> (string)

The Amazon S3 location of your redacted transcript. You can use this URI to access or download your transcript.

If you included OutputBucketName in your transcription job request, this is the URI of that bucket. If you also included OutputKey in your request, your output is located in the path you specified in your request.

If you didn’t include OutputBucketName in your transcription job request, your transcript is stored in a service-managed bucket, and RedactedTranscriptFileUri provides you with a temporary URI you can use for secure access to your transcript.

Note

Temporary URIs for service-managed Amazon S3 buckets are only valid for 15 minutes. If you get an AccesDenied error, you can get a new temporary URI by running a GetTranscriptionJob or ListTranscriptionJob request.

StartTime -> (timestamp)

The date and time the specified transcription job began processing.

Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC . For example, 2022-05-04T12:32:58.789000-07:00 represents a transcription job that started processing at 12:32 PM UTC-7 on May 4, 2022.

CreationTime -> (timestamp)

The date and time the specified transcription job request was made.

Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC . For example, 2022-05-04T12:32:58.761000-07:00 represents a transcription job that started processing at 12:32 PM UTC-7 on May 4, 2022.

CompletionTime -> (timestamp)

The date and time the specified transcription job finished processing.

Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC . For example, 2022-05-04T12:33:13.922000-07:00 represents a transcription job that started processing at 12:33 PM UTC-7 on May 4, 2022.

FailureReason -> (string)

If TranscriptionJobStatus is FAILED , FailureReason contains information about why the transcription job request failed.

The FailureReason field contains one of the following values:

  • Unsupported media format . The media format specified in MediaFormat isn’t valid. Refer to MediaFormat for a list of supported formats.

  • The media format provided does not match the detected media format . The media format specified in MediaFormat doesn’t match the format of the input file. Check the media format of your media file and correct the specified value.

  • Invalid sample rate for audio file . The sample rate specified in MediaSampleRateHertz isn’t valid. The sample rate must be between 8,000 and 48,000 hertz.

  • The sample rate provided does not match the detected sample rate . The sample rate specified in MediaSampleRateHertz doesn’t match the sample rate detected in your input media file. Check the sample rate of your media file and correct the specified value.

  • Invalid file size: file size too large . The size of your media file is larger than what Amazon Transcribe can process. For more information, refer to Guidelines and quotas .

  • Invalid number of channels: number of channels too large . Your audio contains more channels than Amazon Transcribe is able to process. For more information, refer to Guidelines and quotas .

Settings -> (structure)

Provides information on any additional settings that were included in your request. Additional settings include channel identification, alternative transcriptions, speaker partitioning, custom vocabularies, and custom vocabulary filters.

VocabularyName -> (string)

The name of the custom vocabulary you want to use in your transcription job request. This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account.

ShowSpeakerLabels -> (boolean)

Enables speaker partitioning (diarization) in your transcription output. Speaker partitioning labels the speech from individual speakers in your media file.

If you enable ShowSpeakerLabels in your request, you must also include MaxSpeakerLabels .

You can’t include both ShowSpeakerLabels and ChannelIdentification in the same request. Including both parameters returns a BadRequestException .

For more information, see Partitioning speakers (diarization) .

MaxSpeakerLabels -> (integer)

Specify the maximum number of speakers you want to partition in your media.

Note that if your media contains more speakers than the specified number, multiple speakers are treated as a single speaker.

If you specify the MaxSpeakerLabels field, you must set the ShowSpeakerLabels field to true.

ChannelIdentification -> (boolean)

Enables channel identification in multi-channel audio.

Channel identification transcribes the audio on each channel independently, then appends the output for each channel into one transcript.

You can’t include both ShowSpeakerLabels and ChannelIdentification in the same request. Including both parameters returns a BadRequestException .

For more information, see Transcribing multi-channel audio .

ShowAlternatives -> (boolean)

To include alternative transcriptions within your transcription output, include ShowAlternatives in your transcription request.

If you have multi-channel audio and do not enable channel identification, your audio is transcribed in a continuous manner and your transcript does not separate the speech by channel.

If you include ShowAlternatives , you must also include MaxAlternatives , which is the maximum number of alternative transcriptions you want Amazon Transcribe to generate.

For more information, see Alternative transcriptions .

MaxAlternatives -> (integer)

Indicate the maximum number of alternative transcriptions you want Amazon Transcribe to include in your transcript.

If you select a number greater than the number of alternative transcriptions generated by Amazon Transcribe, only the actual number of alternative transcriptions are included.

If you include MaxAlternatives in your request, you must also include ShowAlternatives with a value of true .

For more information, see Alternative transcriptions .

VocabularyFilterName -> (string)

The name of the custom vocabulary filter you want to use in your transcription job request. This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account.

Note that if you include VocabularyFilterName in your request, you must also include VocabularyFilterMethod .

VocabularyFilterMethod -> (string)

Specify how you want your custom vocabulary filter applied to your transcript.

To replace words with *** , choose mask .

To delete words, choose remove .

To flag words without changing them, choose tag .

ModelSettings -> (structure)

Provides information on the custom language model you included in your request.

LanguageModelName -> (string)

The name of the custom language model you want to use when processing your transcription job. Note that custom language model names are case sensitive.

The language of the specified custom language model must match the language code that you specify in your transcription request. If the languages don’t match, the custom language model isn’t applied. There are no errors or warnings associated with a language mismatch.

JobExecutionSettings -> (structure)

Provides information about how your transcription job was processed. This parameter shows if your request was queued and what data access role was used.

AllowDeferredExecution -> (boolean)

Makes it possible to enable job queuing when your concurrent request limit is exceeded. When AllowDeferredExecution is set to true , transcription job requests are placed in a queue until the number of jobs falls below the concurrent request limit. If AllowDeferredExecution is set to false and the number of transcription job requests exceed the concurrent request limit, you get a LimitExceededException error.

Note that job queuing is enabled by default for Call Analytics jobs.

If you include AllowDeferredExecution in your request, you must also include DataAccessRoleArn .

DataAccessRoleArn -> (string)

The Amazon Resource Name (ARN) of an IAM role that has permissions to access the Amazon S3 bucket that contains your input files. If the role that you specify doesn’t have the appropriate permissions to access the specified Amazon S3 location, your request fails.

IAM role ARNs have the format arn:partition:iam::account:role/role-name-with-path . For example: arn:aws:iam::111122223333:role/Admin . For more information, see IAM ARNs .

Note that if you include DataAccessRoleArn in your request, you must also include AllowDeferredExecution .

ContentRedaction -> (structure)

Indicates whether redaction was enabled in your transcript.

RedactionType -> (string)

Specify the category of information you want to redact; PII (personally identifiable information) is the only valid value. You can use PiiEntityTypes to choose which types of PII you want to redact.

RedactionOutput -> (string)

Specify if you want only a redacted transcript, or if you want a redacted and an unredacted transcript.

When you choose redacted Amazon Transcribe creates only a redacted transcript.

When you choose redacted_and_unredacted Amazon Transcribe creates a redacted and an unredacted transcript (as two separate files).

PiiEntityTypes -> (list)

Specify which types of personally identifiable information (PII) you want to redact in your transcript. You can include as many types as you’d like, or you can select ALL .

(string)

IdentifyLanguage -> (boolean)

Indicates whether automatic language identification was enabled (TRUE ) for the specified transcription job.

IdentifyMultipleLanguages -> (boolean)

Indicates whether automatic multi-language identification was enabled (TRUE ) for the specified transcription job.

LanguageOptions -> (list)

Provides the language codes you specified in your request.

(string)

IdentifiedLanguageScore -> (float)

The confidence score associated with the language identified in your media file.

Confidence scores are values between 0 and 1; a larger value indicates a higher probability that the identified language correctly matches the language spoken in your media.

LanguageCodes -> (list)

The language codes used to create your transcription job. This parameter is used with multi-language identification. For single-language identification requests, refer to the singular version of this parameter, LanguageCode .

(structure)

Provides information on the speech contained in a discreet utterance when multi-language identification is enabled in your request. This utterance represents a block of speech consisting of one language, preceded or followed by a block of speech in a different language.

LanguageCode -> (string)

Provides the language code for each language identified in your media.

DurationInSeconds -> (float)

Provides the total time, in seconds, each identified language is spoken in your media.

Tags -> (list)

The tags, each in the form of a key:value pair, assigned to the specified transcription job.

(structure)

Adds metadata, in the form of a key:value pair, to the specified resource.

For example, you could add the tag Department:Sales to a resource to indicate that it pertains to your organization’s sales department. You can also use tags for tag-based access control.

To learn more about tagging, see Tagging resources .

Key -> (string)

The first part of a key:value pair that forms a tag associated with a given resource. For example, in the tag Department:Sales , the key is ‘Department’.

Value -> (string)

The second part of a key:value pair that forms a tag associated with a given resource. For example, in the tag Department:Sales , the value is ‘Sales’.

Note that you can set the value of a tag to an empty string, but you can’t set the value of a tag to null. Omitting the tag value is the same as using an empty string.

Subtitles -> (structure)

Indicates whether subtitles were generated with your transcription.

Formats -> (list)

Provides the format of your subtitle files. If your request included both WebVTT (vtt ) and SubRip (srt ) formats, both formats are shown.

(string)

SubtitleFileUris -> (list)

The Amazon S3 location of your transcript. You can use this URI to access or download your subtitle file. Your subtitle file is stored in the same location as your transcript. If you specified both WebVTT and SubRip subtitle formats, two URIs are provided.

If you included OutputBucketName in your transcription job request, this is the URI of that bucket. If you also included OutputKey in your request, your output is located in the path you specified in your request.

If you didn’t include OutputBucketName in your transcription job request, your subtitle file is stored in a service-managed bucket, and TranscriptFileUri provides you with a temporary URI you can use for secure access to your subtitle file.

Note

Temporary URIs for service-managed Amazon S3 buckets are only valid for 15 minutes. If you get an AccesDenied error, you can get a new temporary URI by running a GetTranscriptionJob or ListTranscriptionJob request.

(string)

OutputStartIndex -> (integer)

Provides the start index value for your subtitle files. If you did not specify a value in your request, the default value of 0 is used.

LanguageIdSettings -> (map)

Provides the name and language of all custom language models, custom vocabularies, and custom vocabulary filters that you included in your request.

key -> (string)

value -> (structure)

If using automatic language identification in your request and you want to apply a custom language model, a custom vocabulary, or a custom vocabulary filter, include LanguageIdSettings with the relevant sub-parameters (VocabularyName , LanguageModelName , and VocabularyFilterName ). Note that multi-language identification (IdentifyMultipleLanguages ) doesn’t support custom language models.

LanguageIdSettings supports two to five language codes. Each language code you include can have an associated custom language model, custom vocabulary, and custom vocabulary filter. The language codes that you specify must match the languages of the associated custom language models, custom vocabularies, and custom vocabulary filters.

It’s recommended that you include LanguageOptions when using LanguageIdSettings to ensure that the correct language dialect is identified. For example, if you specify a custom vocabulary that is in en-US but Amazon Transcribe determines that the language spoken in your media is en-AU , your custom vocabulary is not applied to your transcription. If you include LanguageOptions and include en-US as the only English language dialect, your custom vocabulary is applied to your transcription.

If you want to include a custom language model with your request but do not want to use automatic language identification, use instead the parameter with the LanguageModelName sub-parameter. If you want to include a custom vocabulary or a custom vocabulary filter (or both) with your request but do not want to use automatic language identification, use instead the parameter with the VocabularyName or VocabularyFilterName (or both) sub-parameter.

VocabularyName -> (string)

The name of the custom vocabulary you want to use when processing your transcription job. Custom vocabulary names are case sensitive.

The language of the specified custom vocabulary must match the language code that you specify in your transcription request. If the languages don’t match, the custom vocabulary isn’t applied. There are no errors or warnings associated with a language mismatch.

VocabularyFilterName -> (string)

The name of the custom vocabulary filter you want to use when processing your transcription job. Custom vocabulary filter names are case sensitive.

The language of the specified custom vocabulary filter must match the language code that you specify in your transcription request. If the languages don’t match, the custom vocabulary filter isn’t applied. There are no errors or warnings associated with a language mismatch.

Note that if you include VocabularyFilterName in your request, you must also include VocabularyFilterMethod .

LanguageModelName -> (string)

The name of the custom language model you want to use when processing your transcription job. Note that custom language model names are case sensitive.

The language of the specified custom language model must match the language code that you specify in your transcription request. If the languages don’t match, the custom language model isn’t applied. There are no errors or warnings associated with a language mismatch.

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