This documentation is for Version 1 of the Amazon CLI only. For documentation related to Version 2 of the Amazon CLI, see the Version 2 User Guide.
Amazon Transcribe examples using Amazon CLI
The following code examples show you how to perform actions and implement common scenarios by using the Amazon Command Line Interface with Amazon Transcribe.
Actions are code excerpts from larger programs and must be run in context. While actions show you how to call individual service functions, you can see actions in context in their related scenarios.
Each example includes a link to the complete source code, where you can find instructions on how to set up and run the code in context.
Topics
Actions
The following code example shows how to use create-language-model
.
- Amazon CLI
-
Example 1: To create a custom language model using both training and tuning data.
The following
create-language-model
example creates a custom language model. You can use a custom language model to improve transcription performance for domains such as legal, hospitality, finance, and insurance. For language-code, enter a valid language code. For base-model-name, specify a base model that is best suited for the sample rate of the audio that you want to transcribe with your custom language model. For model-name, specify the name that you want to call the custom language model.aws transcribe create-language-model \ --
language-code
language-code \ --base-model-name
base-model-name \ --model-namecli-clm-example
\ --input-data-config S3Uri="s3://DOC-EXAMPLE-BUCKET/Amazon-S3-Prefix-for-training-data",TuningDataS3Uri="s3://DOC-EXAMPLE-BUCKET/Amazon-S3-Prefix-for-tuning-data",DataAccessRoleArn="arn:aws:iam::AWS-account-number:role/IAM-role-with-permissions-to-create-a-custom-language-model"Output:
{ "LanguageCode": "language-code", "BaseModelName": "base-model-name", "ModelName": "cli-clm-example", "InputDataConfig": { "S3Uri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-Prefix/", "TuningDataS3Uri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-Prefix/", "DataAccessRoleArn": "arn:aws:iam::AWS-account-number:role/IAM-role-with-permissions-create-a-custom-language-model" }, "ModelStatus": "IN_PROGRESS" }
For more information, see Improving Domain-Specific Transcription Accuracy with Custom Language Models
in the Amazon Transcribe Developer Guide. Example 2: To create a custom language model using only training data.
The following
create-language-model
example transcribes your audio file. You can use a custom language model to improve transcription performance for domains such as legal, hospitality, finance, and insurance. For language-code, enter a valid language code. For base-model-name, specify a base model that is best suited for the sample rate of the audio that you want to transcribe with your custom language model. For model-name, specify the name that you want to call the custom language model.aws transcribe create-language-model \ --language-code
en-US
\ --base-model-name
base-model-name \ --model-namecli-clm-example
\ --input-data-config S3Uri="s3://DOC-EXAMPLE-BUCKET/Amazon-S3-Prefix-For-Training-Data",DataAccessRoleArn="arn:aws:iam::AWS-account-number:role/IAM-role-with-permissions-to-create-a-custom-language-model"Output:
{ "LanguageCode": "en-US", "BaseModelName": "base-model-name", "ModelName": "cli-clm-example", "InputDataConfig": { "S3Uri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-Prefix-For-Training-Data/", "DataAccessRoleArn": "arn:aws:iam::your-AWS-account-number:role/IAM-role-with-permissions-to-create-a-custom-language-model" }, "ModelStatus": "IN_PROGRESS" }
For more information, see Improving Domain-Specific Transcription Accuracy with Custom Language Models
in the Amazon Transcribe Developer Guide. -
For API details, see CreateLanguageModel
in Amazon CLI Command Reference.
-
The following code example shows how to use create-medical-vocabulary
.
- Amazon CLI
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To create a medical custom vocabulary
The following
create-medical-vocabulary
example creates a custom vocabulary. To create a custom vocabulary, you must have created a text file with all the terms that you want to transcribe more accurately. For vocabulary-file-uri, specify the Amazon Simple Storage Service (Amazon S3) URI of that text file. For language-code, specify a language code corresponding to the language of your custom vocabulary. For vocabulary-name, specify what you want to call your custom vocabulary.aws transcribe create-medical-vocabulary \ --vocabulary-name
cli-medical-vocab-example
\ --language-code
language-code \ --vocabulary-file-urihttps://DOC-EXAMPLE-BUCKET.AWS-Region.amazonaws.com/the-text-file-for-the-medical-custom-vocabulary.txt
Output:
{ "VocabularyName": "cli-medical-vocab-example", "LanguageCode": "language-code", "VocabularyState": "PENDING" }
For more information, see Medical Custom Vocabularies
in the Amazon Transcribe Developer Guide. -
For API details, see CreateMedicalVocabulary
in Amazon CLI Command Reference.
-
The following code example shows how to use create-vocabulary-filter
.
- Amazon CLI
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To create a vocabulary filter
The following
create-vocabulary-filter
example creates a vocabulary filter that uses a text file that contains a list of words that you wouldn't want to appear in a transcription. For language-code, specify the language code corresponding to the language of your vocabulary filter. For vocabulary-filter-file-uri, specify the Amazon Simple Storage Service (Amazon S3) URI of the text file. For vocabulary-filter-name, specify the name of your vocabulary filter.aws transcribe create-vocabulary-filter \ --
language-code
language-code \ --vocabulary-filter-file-uris3://DOC-EXAMPLE-BUCKET/vocabulary-filter.txt
\ --vocabulary-filter-namecli-vocabulary-filter-example
Output:
{ "VocabularyFilterName": "cli-vocabulary-filter-example", "LanguageCode": "language-code" }
For more information, see Filtering Unwanted Words
in the Amazon Transcribe Developer Guide. -
For API details, see CreateVocabularyFilter
in Amazon CLI Command Reference.
-
The following code example shows how to use create-vocabulary
.
- Amazon CLI
-
To create a custom vocabulary
The following
create-vocabulary
example creates a custom vocabulary. To create a custom vocabulary, you must have created a text file with all the terms that you want to transcribe more accurately. For vocabulary-file-uri, specify the Amazon Simple Storage Service (Amazon S3) URI of that text file. For language-code, specify a language code corresponding to the language of your custom vocabulary. For vocabulary-name, specify what you want to call your custom vocabulary.aws transcribe create-vocabulary \ --
language-code
language-code \ --vocabulary-namecli-vocab-example
\ --vocabulary-file-uris3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/the-text-file-for-the-custom-vocabulary.txt
Output:
{ "VocabularyName": "cli-vocab-example", "LanguageCode": "language-code", "VocabularyState": "PENDING" }
For more information, see Custom Vocabularies
in the Amazon Transcribe Developer Guide. -
For API details, see CreateVocabulary
in Amazon CLI Command Reference.
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The following code example shows how to use delete-language-model
.
- Amazon CLI
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To delete a custom language model
The following
delete-language-model
example deletes a custom language model.aws transcribe delete-language-model \ --
model-name
model-nameThis command produces no output.
For more information, see Improving Domain-Specific Transcription Accuracy with Custom Language Models
in the Amazon Transcribe Developer Guide. -
For API details, see DeleteLanguageModel
in Amazon CLI Command Reference.
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The following code example shows how to use delete-medical-transcription-job
.
- Amazon CLI
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To delete a medical transcription job
The following
delete-medical-transcription-job
example deletes a medical transcription job.aws transcribe delete-medical-transcription-job \ --
medical-transcription-job-name
medical-transcription-job-nameThis command produces no output.
For more information, see DeleteMedicalTranscriptionJob
in the Amazon Transcribe Developer Guide. -
For API details, see DeleteMedicalTranscriptionJob
in Amazon CLI Command Reference.
-
The following code example shows how to use delete-medical-vocabulary
.
- Amazon CLI
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To delete a medical custom vocabulary
The following
delete-medical-vocabulary
example deletes a medical custom vocabulary. For vocabulary-name, specify the name of the medical custom vocabulary.aws transcribe delete-vocabulary \ --vocabulary-name
medical-custom-vocabulary-name
This command produces no output.
For more information, see Medical Custom Vocabularies
in the Amazon Transcribe Developer Guide. -
For API details, see DeleteMedicalVocabulary
in Amazon CLI Command Reference.
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The following code example shows how to use delete-transcription-job
.
- Amazon CLI
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To delete one of your transcription jobs
The following
delete-transcription-job
example deletes one of your transcription jobs.aws transcribe delete-transcription-job \ --transcription-job-name
your-transcription-job
This command produces no output.
For more information, see DeleteTranscriptionJob
in the Amazon Transcribe Developer Guide. -
For API details, see DeleteTranscriptionJob
in Amazon CLI Command Reference.
-
The following code example shows how to use delete-vocabulary-filter
.
- Amazon CLI
-
To delete a vocabulary filter
The following
delete-vocabulary-filter
example deletes a vocabulary filter.aws transcribe delete-vocabulary-filter \ --
vocabulary-filter-name
vocabulary-filter-nameThis command produces no output.
For more information, see Filtering Unwanted Words
in the Amazon Transcribe Developer Guide. -
For API details, see DeleteVocabularyFilter
in Amazon CLI Command Reference.
-
The following code example shows how to use delete-vocabulary
.
- Amazon CLI
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To delete a custom vocabulary
The following
delete-vocabulary
example deletes a custom vocabulary.aws transcribe delete-vocabulary \ --
vocabulary-name
vocabulary-nameThis command produces no output.
For more information, see Custom Vocabularies
in the Amazon Transcribe Developer Guide. -
For API details, see DeleteVocabulary
in Amazon CLI Command Reference.
-
The following code example shows how to use describe-language-model
.
- Amazon CLI
-
To get information about a specific custom language model
The following
describe-language-model
example gets information about a specific custom language model. For example, under BaseModelName you can see whether your model is trained using a NarrowBand or WideBand model. Custom language models with a NarrowBand base model can transcribe audio with a sample rate less than 16 kHz. Language models using a WideBand base model can transcribe audio with a sample rate greater than 16 kHz. The S3Uri parameter indicates the Amazon S3 prefix you've used to access the training data to create the custom language model.aws transcribe describe-language-model \ --model-name
cli-clm-example
Output:
{ "LanguageModel": { "ModelName": "cli-clm-example", "CreateTime": "2020-09-25T17:57:38.504000+00:00", "LastModifiedTime": "2020-09-25T17:57:48.585000+00:00", "LanguageCode": "language-code", "BaseModelName": "base-model-name", "ModelStatus": "IN_PROGRESS", "UpgradeAvailability": false, "InputDataConfig": { "S3Uri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-Prefix/", "TuningDataS3Uri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-Prefix/", "DataAccessRoleArn": "arn:aws:iam::AWS-account-number:role/IAM-role-with-permissions-to-create-a-custom-language-model" } } }
For more information, see Improving Domain-Specific Transcription Accuracy with Custom Language Models
in the Amazon Transcribe Developer Guide. -
For API details, see DescribeLanguageModel
in Amazon CLI Command Reference.
-
The following code example shows how to use get-medical-transcription-job
.
- Amazon CLI
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To get information about a specific medical transcription job
The following
get-medical-transcription-job
example gets information about a specific medical transcription job. To access the transcription results, use the TranscriptFileUri parameter. If you've enabled additional features for the transcription job, you can see them in the Settings object. The Specialty parameter shows the medical specialty of the provider. The Type parameter indicates whether the speech in the transcription job is of a medical conversation, or a medical dictation.aws transcribe get-medical-transcription-job \ --medical-transcription-job-name
vocabulary-dictation-medical-transcription-job
Output:
{ "MedicalTranscriptionJob": { "MedicalTranscriptionJobName": "vocabulary-dictation-medical-transcription-job", "TranscriptionJobStatus": "COMPLETED", "LanguageCode": "en-US", "MediaSampleRateHertz": 48000, "MediaFormat": "mp4", "Media": { "MediaFileUri": "s3://Amazon-S3-Prefix/your-audio-file.file-extension" }, "Transcript": { "TranscriptFileUri": "https://s3.Region.amazonaws.com/Amazon-S3-Prefix/vocabulary-dictation-medical-transcription-job.json" }, "StartTime": "2020-09-21T21:17:27.045000+00:00", "CreationTime": "2020-09-21T21:17:27.016000+00:00", "CompletionTime": "2020-09-21T21:17:59.561000+00:00", "Settings": { "ChannelIdentification": false, "ShowAlternatives": false, "VocabularyName": "cli-medical-vocab-example" }, "Specialty": "PRIMARYCARE", "Type": "DICTATION" } }
For more information, see Batch Transcription
in the Amazon Transcribe Developer Guide. -
For API details, see GetMedicalTranscriptionJob
in Amazon CLI Command Reference.
-
The following code example shows how to use get-medical-vocabulary
.
- Amazon CLI
-
To get information about a medical custom vocabulary
The following
get-medical-vocabulary
example gets information on a medical custom vocabulary. You can use the VocabularyState parameter to see the processing state of the vocabulary. If it's READY, you can use it in the StartMedicalTranscriptionJob operation.:aws transcribe get-medical-vocabulary \ --vocabulary-name
medical-vocab-example
Output:
{ "VocabularyName": "medical-vocab-example", "LanguageCode": "en-US", "VocabularyState": "READY", "LastModifiedTime": "2020-09-19T23:59:04.349000+00:00", "DownloadUri": "https://link-to-download-the-text-file-used-to-create-your-medical-custom-vocabulary" }
For more information, see Medical Custom Vocabularies
in the Amazon Transcribe Developer Guide. -
For API details, see GetMedicalVocabulary
in Amazon CLI Command Reference.
-
The following code example shows how to use get-transcription-job
.
- Amazon CLI
-
To get information about a specific transcription job
The following
get-transcription-job
example gets information about a specific transcription job. To access the transcription results, use the TranscriptFileUri parameter. Use the MediaFileUri parameter to see which audio file you transcribed with this job. You can use the Settings object to see the optional features you've enabled in the transcription job.aws transcribe get-transcription-job \ --transcription-job-name
your-transcription-job
Output:
{ "TranscriptionJob": { "TranscriptionJobName": "your-transcription-job", "TranscriptionJobStatus": "COMPLETED", "LanguageCode": "language-code", "MediaSampleRateHertz": 48000, "MediaFormat": "mp4", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.file-extension" }, "Transcript": { "TranscriptFileUri": "https://Amazon-S3-file-location-of-transcription-output" }, "StartTime": "2020-09-18T22:27:23.970000+00:00", "CreationTime": "2020-09-18T22:27:23.948000+00:00", "CompletionTime": "2020-09-18T22:28:21.197000+00:00", "Settings": { "ChannelIdentification": false, "ShowAlternatives": false }, "IdentifyLanguage": true, "IdentifiedLanguageScore": 0.8672199249267578 } }
For more information, see Getting Started (Amazon Command Line Interface)
in the Amazon Transcribe Developer Guide. -
For API details, see GetTranscriptionJob
in Amazon CLI Command Reference.
-
The following code example shows how to use get-vocabulary-filter
.
- Amazon CLI
-
To get information about a vocabulary filter
The following
get-vocabulary-filter
example gets information about a vocabulary filter. You can use the DownloadUri parameter to get the list of words you used to create the vocabulary filter.aws transcribe get-vocabulary-filter \ --vocabulary-filter-name
testFilter
Output:
{ "VocabularyFilterName": "testFilter", "LanguageCode": "language-code", "LastModifiedTime": "2020-05-07T22:39:32.147000+00:00", "DownloadUri": "https://Amazon-S3-location-to-download-your-vocabulary-filter" }
For more information, see Filter Unwanted Words
in the Amazon Transcribe Developer Guide. -
For API details, see GetVocabularyFilter
in Amazon CLI Command Reference.
-
The following code example shows how to use get-vocabulary
.
- Amazon CLI
-
To get information about a custom vocabulary
The following
get-vocabulary
example gets information on a previously created custom vocabulary.aws transcribe get-vocabulary \ --vocabulary-name
cli-vocab-1
Output:
{ "VocabularyName": "cli-vocab-1", "LanguageCode": "language-code", "VocabularyState": "READY", "LastModifiedTime": "2020-09-19T23:22:32.836000+00:00", "DownloadUri": "https://link-to-download-the-text-file-used-to-create-your-custom-vocabulary" }
For more information, see Custom Vocabularies
in the Amazon Transcribe Developer Guide. -
For API details, see GetVocabulary
in Amazon CLI Command Reference.
-
The following code example shows how to use list-language-models
.
- Amazon CLI
-
To list your custom language models
The following
list-language-models
example lists the custom language models associated with your Amazon account and Region. You can use theS3Uri
andTuningDataS3Uri
parameters to find the Amazon S3 prefixes you've used as your training data, or your tuning data. The BaseModelName tells you whether you've used a NarrowBand, or WideBand model to create a custom language model. You can transcribe audio with a sample rate of less than 16 kHz with a custom language model using a NarrowBand base model. You can transcribe audio 16 kHz or greater with a custom language model using a WideBand base model. TheModelStatus
parameter shows whether you can use the custom language model in a transcription job. If the value is COMPLETED, you can use it in a transcription job.aws transcribe list-language-models
Output:
{ "Models": [ { "ModelName": "cli-clm-2", "CreateTime": "2020-09-25T17:57:38.504000+00:00", "LastModifiedTime": "2020-09-25T17:57:48.585000+00:00", "LanguageCode": "language-code", "BaseModelName": "WideBand", "ModelStatus": "IN_PROGRESS", "UpgradeAvailability": false, "InputDataConfig": { "S3Uri": "s3://DOC-EXAMPLE-BUCKET/clm-training-data/", "TuningDataS3Uri": "s3://DOC-EXAMPLE-BUCKET/clm-tuning-data/", "DataAccessRoleArn": "arn:aws:iam::AWS-account-number:role/IAM-role-used-to-create-the-custom-language-model" } }, { "ModelName": "cli-clm-1", "CreateTime": "2020-09-25T17:16:01.835000+00:00", "LastModifiedTime": "2020-09-25T17:16:15.555000+00:00", "LanguageCode": "language-code", "BaseModelName": "WideBand", "ModelStatus": "IN_PROGRESS", "UpgradeAvailability": false, "InputDataConfig": { "S3Uri": "s3://DOC-EXAMPLE-BUCKET/clm-training-data/", "DataAccessRoleArn": "arn:aws:iam::AWS-account-number:role/IAM-role-used-to-create-the-custom-language-model" } }, { "ModelName": "clm-console-1", "CreateTime": "2020-09-24T19:26:28.076000+00:00", "LastModifiedTime": "2020-09-25T04:25:22.271000+00:00", "LanguageCode": "language-code", "BaseModelName": "NarrowBand", "ModelStatus": "COMPLETED", "UpgradeAvailability": false, "InputDataConfig": { "S3Uri": "s3://DOC-EXAMPLE-BUCKET/clm-training-data/", "DataAccessRoleArn": "arn:aws:iam::AWS-account-number:role/IAM-role-used-to-create-the-custom-language-model" } } ] }
For more information, see Improving Domain-Specific Transcription Accuracy with Custom Language Models
in the Amazon Transcribe Developer Guide. -
For API details, see ListLanguageModels
in Amazon CLI Command Reference.
-
The following code example shows how to use list-medical-transcription-jobs
.
- Amazon CLI
-
To list your medical transcription jobs
The following
list-medical-transcription-jobs
example lists the medical transcription jobs associated with your Amazon account and Region. To get more information about a particular transcription job, copy the value of a MedicalTranscriptionJobName parameter in the transcription output, and specify that value for theMedicalTranscriptionJobName
option of theget-medical-transcription-job
command. To see more of your transcription jobs, copy the value of the NextToken parameter, run thelist-medical-transcription-jobs
command again, and specify that value in the--next-token
option.aws transcribe list-medical-transcription-jobs
Output:
{ "NextToken": "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", "MedicalTranscriptionJobSummaries": [ { "MedicalTranscriptionJobName": "vocabulary-dictation-medical-transcription-job", "CreationTime": "2020-09-21T21:17:27.016000+00:00", "StartTime": "2020-09-21T21:17:27.045000+00:00", "CompletionTime": "2020-09-21T21:17:59.561000+00:00", "LanguageCode": "en-US", "TranscriptionJobStatus": "COMPLETED", "OutputLocationType": "CUSTOMER_BUCKET", "Specialty": "PRIMARYCARE", "Type": "DICTATION" }, { "MedicalTranscriptionJobName": "alternatives-dictation-medical-transcription-job", "CreationTime": "2020-09-21T21:01:14.569000+00:00", "StartTime": "2020-09-21T21:01:14.592000+00:00", "CompletionTime": "2020-09-21T21:01:43.606000+00:00", "LanguageCode": "en-US", "TranscriptionJobStatus": "COMPLETED", "OutputLocationType": "CUSTOMER_BUCKET", "Specialty": "PRIMARYCARE", "Type": "DICTATION" }, { "MedicalTranscriptionJobName": "alternatives-conversation-medical-transcription-job", "CreationTime": "2020-09-21T19:09:18.171000+00:00", "StartTime": "2020-09-21T19:09:18.199000+00:00", "CompletionTime": "2020-09-21T19:10:22.516000+00:00", "LanguageCode": "en-US", "TranscriptionJobStatus": "COMPLETED", "OutputLocationType": "CUSTOMER_BUCKET", "Specialty": "PRIMARYCARE", "Type": "CONVERSATION" }, { "MedicalTranscriptionJobName": "speaker-id-conversation-medical-transcription-job", "CreationTime": "2020-09-21T18:43:37.157000+00:00", "StartTime": "2020-09-21T18:43:37.265000+00:00", "CompletionTime": "2020-09-21T18:44:21.192000+00:00", "LanguageCode": "en-US", "TranscriptionJobStatus": "COMPLETED", "OutputLocationType": "CUSTOMER_BUCKET", "Specialty": "PRIMARYCARE", "Type": "CONVERSATION" }, { "MedicalTranscriptionJobName": "multichannel-conversation-medical-transcription-job", "CreationTime": "2020-09-20T23:46:44.053000+00:00", "StartTime": "2020-09-20T23:46:44.081000+00:00", "CompletionTime": "2020-09-20T23:47:35.851000+00:00", "LanguageCode": "en-US", "TranscriptionJobStatus": "COMPLETED", "OutputLocationType": "CUSTOMER_BUCKET", "Specialty": "PRIMARYCARE", "Type": "CONVERSATION" } ] }
For more information, see https://docs.aws.amazon.com/transcribe/latest/dg/batch-med-transcription.html> in the Amazon Transcribe Developer Guide.
-
For API details, see ListMedicalTranscriptionJobs
in Amazon CLI Command Reference.
-
The following code example shows how to use list-medical-vocabularies
.
- Amazon CLI
-
To list your medical custom vocabularies
The following
list-medical-vocabularies
example lists the medical custom vocabularies associated with your Amazon account and Region. To get more information about a particular transcription job, copy the value of aMedicalTranscriptionJobName
parameter in the transcription output, and specify that value for theMedicalTranscriptionJobName
option of theget-medical-transcription-job
command. To see more of your transcription jobs, copy the value of theNextToken
parameter, run thelist-medical-transcription-jobs
command again, and specify that value in the--next-token
option.aws transcribe list-medical-vocabularies
Output:
{ "Vocabularies": [ { "VocabularyName": "cli-medical-vocab-2", "LanguageCode": "en-US", "LastModifiedTime": "2020-09-21T21:44:59.521000+00:00", "VocabularyState": "READY" }, { "VocabularyName": "cli-medical-vocab-1", "LanguageCode": "en-US", "LastModifiedTime": "2020-09-19T23:59:04.349000+00:00", "VocabularyState": "READY" } ] }
For more information, see Medical Custom Vocabularies
in the Amazon Transcribe Developer Guide. -
For API details, see ListMedicalVocabularies
in Amazon CLI Command Reference.
-
The following code example shows how to use list-transcription-jobs
.
- Amazon CLI
-
To list your transcription jobs
The following
list-transcription-jobs
example lists the transcription jobs associated with your Amazon account and Region.aws transcribe list-transcription-jobs
Output:
{ "NextToken": "NextToken", "TranscriptionJobSummaries": [ { "TranscriptionJobName": "speak-id-job-1", "CreationTime": "2020-08-17T21:06:15.391000+00:00", "StartTime": "2020-08-17T21:06:15.416000+00:00", "CompletionTime": "2020-08-17T21:07:05.098000+00:00", "LanguageCode": "language-code", "TranscriptionJobStatus": "COMPLETED", "OutputLocationType": "SERVICE_BUCKET" }, { "TranscriptionJobName": "job-1", "CreationTime": "2020-08-17T20:50:24.207000+00:00", "StartTime": "2020-08-17T20:50:24.230000+00:00", "CompletionTime": "2020-08-17T20:52:18.737000+00:00", "LanguageCode": "language-code", "TranscriptionJobStatus": "COMPLETED", "OutputLocationType": "SERVICE_BUCKET" }, { "TranscriptionJobName": "sdk-test-job-4", "CreationTime": "2020-08-17T20:32:27.917000+00:00", "StartTime": "2020-08-17T20:32:27.956000+00:00", "CompletionTime": "2020-08-17T20:33:15.126000+00:00", "LanguageCode": "language-code", "TranscriptionJobStatus": "COMPLETED", "OutputLocationType": "SERVICE_BUCKET" }, { "TranscriptionJobName": "Diarization-speak-id", "CreationTime": "2020-08-10T22:10:09.066000+00:00", "StartTime": "2020-08-10T22:10:09.116000+00:00", "CompletionTime": "2020-08-10T22:26:48.172000+00:00", "LanguageCode": "language-code", "TranscriptionJobStatus": "COMPLETED", "OutputLocationType": "SERVICE_BUCKET" }, { "TranscriptionJobName": "your-transcription-job-name", "CreationTime": "2020-07-29T17:45:09.791000+00:00", "StartTime": "2020-07-29T17:45:09.826000+00:00", "CompletionTime": "2020-07-29T17:46:20.831000+00:00", "LanguageCode": "language-code", "TranscriptionJobStatus": "COMPLETED", "OutputLocationType": "SERVICE_BUCKET" } ] }
For more information, see Getting Started (Amazon Command Line Interface)
in the Amazon Transcribe Developer Guide. -
For API details, see ListTranscriptionJobs
in Amazon CLI Command Reference.
-
The following code example shows how to use list-vocabularies
.
- Amazon CLI
-
To list your custom vocabularies
The following
list-vocabularies
example lists the custom vocabularies associated with your Amazon account and Region.aws transcribe list-vocabularies
Output:
{ "NextToken": "NextToken", "Vocabularies": [ { "VocabularyName": "ards-test-1", "LanguageCode": "language-code", "LastModifiedTime": "2020-04-27T22:00:27.330000+00:00", "VocabularyState": "READY" }, { "VocabularyName": "sample-test", "LanguageCode": "language-code", "LastModifiedTime": "2020-04-24T23:04:11.044000+00:00", "VocabularyState": "READY" }, { "VocabularyName": "CRLF-to-LF-test-3-1", "LanguageCode": "language-code", "LastModifiedTime": "2020-04-24T22:12:22.277000+00:00", "VocabularyState": "READY" }, { "VocabularyName": "CRLF-to-LF-test-2", "LanguageCode": "language-code", "LastModifiedTime": "2020-04-24T21:53:50.455000+00:00", "VocabularyState": "READY" }, { "VocabularyName": "CRLF-to-LF-1-1", "LanguageCode": "language-code", "LastModifiedTime": "2020-04-24T21:39:33.356000+00:00", "VocabularyState": "READY" } ] }
For more information, see Custom Vocabularies
in the Amazon Transcribe Developer Guide. -
For API details, see ListVocabularies
in Amazon CLI Command Reference.
-
The following code example shows how to use list-vocabulary-filters
.
- Amazon CLI
-
To list your vocabulary filters
The following
list-vocabulary-filters
example lists the vocabulary filters associated with your Amazon account and Region.aws transcribe list-vocabulary-filters
Output:
{ "NextToken": "NextToken": [ { "VocabularyFilterName": "testFilter", "LanguageCode": "language-code", "LastModifiedTime": "2020-05-07T22:39:32.147000+00:00" }, { "VocabularyFilterName": "testFilter2", "LanguageCode": "language-code", "LastModifiedTime": "2020-05-21T23:29:35.174000+00:00" }, { "VocabularyFilterName": "filter2", "LanguageCode": "language-code", "LastModifiedTime": "2020-05-08T20:18:26.426000+00:00" }, { "VocabularyFilterName": "filter-review", "LanguageCode": "language-code", "LastModifiedTime": "2020-06-03T18:52:30.448000+00:00" }, { "VocabularyFilterName": "crlf-filt", "LanguageCode": "language-code", "LastModifiedTime": "2020-05-22T19:42:42.737000+00:00" } ] }
For more information, see Filtering Unwanted Words
in the Amazon Transcribe Developer Guide. -
For API details, see ListVocabularyFilters
in Amazon CLI Command Reference.
-
The following code example shows how to use start-medical-transcription-job
.
- Amazon CLI
-
Example 1: To transcribe a medical dictation stored as an audio file
The following
start-medical-transcription-job
example transcribes an audio file. You specify the location of the transcription output in theOutputBucketName
parameter.aws transcribe start-medical-transcription-job \ --cli-input-json
file://myfile.json
Contents of
myfile.json
:{ "MedicalTranscriptionJobName": "simple-dictation-medical-transcription-job", "LanguageCode": "language-code", "Specialty": "PRIMARYCARE", "Type": "DICTATION", "OutputBucketName":"DOC-EXAMPLE-BUCKET", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.extension" } }
Output:
{ "MedicalTranscriptionJob": { "MedicalTranscriptionJobName": "simple-dictation-medical-transcription-job", "TranscriptionJobStatus": "IN_PROGRESS", "LanguageCode": "language-code", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.extension" }, "StartTime": "2020-09-20T00:35:22.256000+00:00", "CreationTime": "2020-09-20T00:35:22.218000+00:00", "Specialty": "PRIMARYCARE", "Type": "DICTATION" } }
For more information, see Batch Transcription Overview
in the Amazon Transcribe Developer Guide. Example 2: To transcribe a clinician-patient dialogue stored as an audio file
The following
start-medical-transcription-job
example transcribes an audio file containing a clinician-patient dialogue. You specify the location of the transcription output in the OutputBucketName parameter.aws transcribe start-medical-transcription-job \ --cli-input-json
file://mysecondfile.json
Contents of
mysecondfile.json
:{ "MedicalTranscriptionJobName": "simple-dictation-medical-transcription-job", "LanguageCode": "language-code", "Specialty": "PRIMARYCARE", "Type": "CONVERSATION", "OutputBucketName":"DOC-EXAMPLE-BUCKET", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.extension" } }
Output:
{ "MedicalTranscriptionJob": { "MedicalTranscriptionJobName": "simple-conversation-medical-transcription-job", "TranscriptionJobStatus": "IN_PROGRESS", "LanguageCode": "language-code", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.extension" }, "StartTime": "2020-09-20T23:19:49.965000+00:00", "CreationTime": "2020-09-20T23:19:49.941000+00:00", "Specialty": "PRIMARYCARE", "Type": "CONVERSATION" } }
For more information, see Batch Transcription Overview
in the Amazon Transcribe Developer Guide. Example 3: To transcribe a multichannel audio file of a clinician-patient dialogue
The following
start-medical-transcription-job
example transcribes the audio from each channel in the audio file and merges the separate transcriptions from each channel into a single transcription output. You specify the location of the transcription output in theOutputBucketName
parameter.aws transcribe start-medical-transcription-job \ --cli-input-json
file://mythirdfile.json
Contents of
mythirdfile.json
:{ "MedicalTranscriptionJobName": "multichannel-conversation-medical-transcription-job", "LanguageCode": "language-code", "Specialty": "PRIMARYCARE", "Type": "CONVERSATION", "OutputBucketName":"DOC-EXAMPLE-BUCKET", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.extension" }, "Settings":{ "ChannelIdentification": true } }
Output:
{ "MedicalTranscriptionJob": { "MedicalTranscriptionJobName": "multichannel-conversation-medical-transcription-job", "TranscriptionJobStatus": "IN_PROGRESS", "LanguageCode": "language-code", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.extension" }, "StartTime": "2020-09-20T23:46:44.081000+00:00", "CreationTime": "2020-09-20T23:46:44.053000+00:00", "Settings": { "ChannelIdentification": true }, "Specialty": "PRIMARYCARE", "Type": "CONVERSATION" } }
For more information, see Channel Identification
in the Amazon Transcribe Developer Guide. Example 4: To transcribe an audio file of a clinician-patient dialogue and identify the speakers in the transcription output
The following
start-medical-transcription-job
example transcribes an audio file and labels the speech of each speaker in the transcription output. You specify the location of the transcription output in theOutputBucketName
parameter.aws transcribe start-medical-transcription-job \ --cli-input-json
file://myfourthfile.json
Contents of
myfourthfile.json
:{ "MedicalTranscriptionJobName": "speaker-id-conversation-medical-transcription-job", "LanguageCode": "language-code", "Specialty": "PRIMARYCARE", "Type": "CONVERSATION", "OutputBucketName":"DOC-EXAMPLE-BUCKET", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.extension" }, "Settings":{ "ShowSpeakerLabels": true, "MaxSpeakerLabels": 2 } }
Output:
{ "MedicalTranscriptionJob": { "MedicalTranscriptionJobName": "speaker-id-conversation-medical-transcription-job", "TranscriptionJobStatus": "IN_PROGRESS", "LanguageCode": "language-code", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.extension" }, "StartTime": "2020-09-21T18:43:37.265000+00:00", "CreationTime": "2020-09-21T18:43:37.157000+00:00", "Settings": { "ShowSpeakerLabels": true, "MaxSpeakerLabels": 2 }, "Specialty": "PRIMARYCARE", "Type": "CONVERSATION" } }
For more information, see Identifying Speakers
in the Amazon Transcribe Developer Guide. Example 5: To transcribe a medical conversation stored as an audio file with up to two transcription alternatives
The following
start-medical-transcription-job
example creates up to two alternative transcriptions from a single audio file. Every transcriptions has a level of confidence associated with it. By default, Amazon Transcribe returns the transcription with the highest confidence level. You can specify that Amazon Transcribe return additional transcriptions with lower confidence levels. You specify the location of the transcription output in theOutputBucketName
parameter.aws transcribe start-medical-transcription-job \ --cli-input-json
file://myfifthfile.json
Contents of
myfifthfile.json
:{ "MedicalTranscriptionJobName": "alternatives-conversation-medical-transcription-job", "LanguageCode": "language-code", "Specialty": "PRIMARYCARE", "Type": "CONVERSATION", "OutputBucketName":"DOC-EXAMPLE-BUCKET", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.extension" }, "Settings":{ "ShowAlternatives": true, "MaxAlternatives": 2 } }
Output:
{ "MedicalTranscriptionJob": { "MedicalTranscriptionJobName": "alternatives-conversation-medical-transcription-job", "TranscriptionJobStatus": "IN_PROGRESS", "LanguageCode": "language-code", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.extension" }, "StartTime": "2020-09-21T19:09:18.199000+00:00", "CreationTime": "2020-09-21T19:09:18.171000+00:00", "Settings": { "ShowAlternatives": true, "MaxAlternatives": 2 }, "Specialty": "PRIMARYCARE", "Type": "CONVERSATION" } }
For more information, see Alternative Transcriptions
in the Amazon Transcribe Developer Guide. Example 6: To transcribe an audio file of a medical dictation with up to two alternative transcriptions
The following
start-medical-transcription-job
example transcribes an audio file and uses a vocabulary filter to mask any unwanted words. You specify the location of the transcription output in the OutputBucketName parameter.aws transcribe start-medical-transcription-job \ --cli-input-json
file://mysixthfile.json
Contents of
mysixthfile.json
:{ "MedicalTranscriptionJobName": "alternatives-conversation-medical-transcription-job", "LanguageCode": "language-code", "Specialty": "PRIMARYCARE", "Type": "DICTATION", "OutputBucketName":"DOC-EXAMPLE-BUCKET", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.extension" }, "Settings":{ "ShowAlternatives": true, "MaxAlternatives": 2 } }
Output:
{ "MedicalTranscriptionJob": { "MedicalTranscriptionJobName": "alternatives-dictation-medical-transcription-job", "TranscriptionJobStatus": "IN_PROGRESS", "LanguageCode": "language-code", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.extension" }, "StartTime": "2020-09-21T21:01:14.592000+00:00", "CreationTime": "2020-09-21T21:01:14.569000+00:00", "Settings": { "ShowAlternatives": true, "MaxAlternatives": 2 }, "Specialty": "PRIMARYCARE", "Type": "DICTATION" } }
For more information, see Alternative Transcriptions
in the Amazon Transcribe Developer Guide. Example 7: To transcribe an audio file of a medical dictation with increased accuracy by using a custom vocabulary
The following
start-medical-transcription-job
example transcribes an audio file and uses a medical custom vocabulary you've previously created to increase the transcription accuracy. You specify the location of the transcription output in theOutputBucketName
parameter.aws transcribe start-transcription-job \ --cli-input-json
file://myseventhfile.json
Contents of
mysixthfile.json
:{ "MedicalTranscriptionJobName": "vocabulary-dictation-medical-transcription-job", "LanguageCode": "language-code", "Specialty": "PRIMARYCARE", "Type": "DICTATION", "OutputBucketName":"DOC-EXAMPLE-BUCKET", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.extension" }, "Settings":{ "VocabularyName": "cli-medical-vocab-1" } }
Output:
{ "MedicalTranscriptionJob": { "MedicalTranscriptionJobName": "vocabulary-dictation-medical-transcription-job", "TranscriptionJobStatus": "IN_PROGRESS", "LanguageCode": "language-code", "Media": { "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.extension" }, "StartTime": "2020-09-21T21:17:27.045000+00:00", "CreationTime": "2020-09-21T21:17:27.016000+00:00", "Settings": { "VocabularyName": "cli-medical-vocab-1" }, "Specialty": "PRIMARYCARE", "Type": "DICTATION" } }
For more information, see Medical Custom Vocabularies
in the Amazon Transcribe Developer Guide. -
For API details, see StartMedicalTranscriptionJob
in Amazon CLI Command Reference.
-
The following code example shows how to use start-transcription-job
.
- Amazon CLI
-
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 (Amazon 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. -
For API details, see StartTranscriptionJob
in Amazon CLI Command Reference.
-
The following code example shows how to use update-medical-vocabulary
.
- Amazon CLI
-
To update a medical custom vocabulary with new terms.
The following
update-medical-vocabulary
example replaces the terms used in a medical custom vocabulary with the new ones. Prerequisite: to replace the terms in a medical custom vocabulary, you need a file with new terms.aws transcribe update-medical-vocabulary \ --vocabulary-file-uri
s3://DOC-EXAMPLE-BUCKET/Amazon-S3-Prefix/medical-custom-vocabulary.txt
\ --vocabulary-namemedical-custom-vocabulary
\ --language
-code languageOutput:
{ "VocabularyName": "medical-custom-vocabulary", "LanguageCode": "en-US", "VocabularyState": "PENDING" }
For more information, see Medical Custom Vocabularies
in the Amazon Transcribe Developer Guide. -
For API details, see UpdateMedicalVocabulary
in Amazon CLI Command Reference.
-
The following code example shows how to use update-vocabulary-filter
.
- Amazon CLI
-
To replace the words in a vocabulary filter
The following
update-vocabulary-filter
example replaces the words in a vocabulary filter with new ones. Prerequisite: To update a vocabulary filter with the new words, you must have those words saved as a text file.aws transcribe update-vocabulary-filter \ --vocabulary-filter-file-uri
s3://DOC-EXAMPLE-BUCKET/Amazon-S3-Prefix/your-text-file-to-update-your-vocabulary-filter.txt
\ --vocabulary-filter-name
vocabulary-filter-nameOutput:
{ "VocabularyFilterName": "vocabulary-filter-name", "LanguageCode": "language-code", "LastModifiedTime": "2020-09-23T18:40:35.139000+00:00" }
For more information, see Filtering Unwanted Words
in the Amazon Transcribe Developer Guide. -
For API details, see UpdateVocabularyFilter
in Amazon CLI Command Reference.
-
The following code example shows how to use update-vocabulary
.
- Amazon CLI
-
To update a custom vocabulary with new terms.
The following
update-vocabulary
example overwrites the terms used to create a custom vocabulary with the new ones that you provide. Prerequisite: to replace the terms in a custom vocabulary, you need a file with new terms.aws transcribe update-vocabulary \ --vocabulary-file-uri
s3://DOC-EXAMPLE-BUCKET/Amazon-S3-Prefix/custom-vocabulary.txt
\ --vocabulary-namecustom-vocabulary
\ --language-code
language-codeOutput:
{ "VocabularyName": "custom-vocabulary", "LanguageCode": "language", "VocabularyState": "PENDING" }
For more information, see Custom Vocabularies
in the Amazon Transcribe Developer Guide. -
For API details, see UpdateVocabulary
in Amazon CLI Command Reference.
-