Creating a custom vocabulary using a list

Important

Custom vocabularies in list format are being deprecated, so if you're creating a new custom vocabulary, we strongly recommend using the table format.

You can create custom vocabularies from lists using the AWS Management Console, AWS CLI, or AWS SDKs.

• AWS Management Console: You must create and upload a text file containing your custom vocabulary. You can use line-separated or comma-separated entries. Note that your list must be saved as a text (*.txt) file in LF format. If you use any other format, such as CRLF, your custom vocabulary is not accepted by Amazon Transcribe.

• AWS CLI and AWS SDKs: You must include your custom vocabulary as comma-separated entries within your API call using the Phrases flag.

If an entry contains multiple words, you must hyphenate each word. For example, you include 'Los Angeles' as Los-Angeles and 'Andorra la Vella' as Andorra-la-Vella.

Here are examples of the two valid list formats. Refer to Creating custom vocabulary lists for method-specific examples.

• Comma-separated entries:

  Los-Angeles,CLI,Eva-Maria,ABCs,Andorra-la-Vella

• Line-separated entries:

  Los-Angeles
  CLI
  Eva-Maria
  ABCs
  Andorra-la-Vella

Important

You can only use characters that are supported for your language. Refer to your language's character set for details.

Custom vocabulary lists are not supported with the CreateMedicalVocabulary operation. If creating a custom medical vocabulary, you must use a table format; refer to Creating a custom vocabulary using a table for instructions.

Creating custom vocabulary lists

To process a custom vocabulary list for use with Amazon Transcribe, see the following examples:

AWS CLI

This example uses the create-vocabulary command with a list-formatted custom vocabulary file. For more information, see CreateVocabulary.

aws transcribe create-vocabulary \ 
--vocabulary-name my-first-vocabulary \ 
--language-code en-US \ 
--phrases {CLI,Eva-Maria,ABCs}

Here's another example using the create-vocabulary command, and a request body that creates your custom vocabulary.

aws transcribe create-vocabulary \
--cli-input-json file://filepath/my-first-vocab-list.json

The file my-first-vocab-list.json contains the following request body.

{
  "VocabularyName": "my-first-vocabulary",
  "LanguageCode": "en-US",
  "Phrases": [
        "CLI","Eva-Maria","ABCs"
  ]
}

Once VocabularyState changes from PENDING to READY, your custom vocabulary is ready to use with a transcription. To view the current status of your custom vocabulary, run:

aws transcribe get-vocabulary \
--vocabulary-name my-first-vocabulary

AWS SDK for Python (Boto3)

This example uses the AWS SDK for Python (Boto3) to create a custom vocabulary from a list using the create_vocabulary method. For more information, see CreateVocabulary.

For additional examples using the AWS SDKs, including feature-specific, scenario, and cross-service examples, refer to the Code examples for Amazon Transcribe using AWS SDKs chapter.

from __future__ import print_function
import time
import boto3
transcribe = boto3.client('transcribe', 'us-west-2')
vocab_name = "my-first-vocabulary"
response = transcribe.create_vocabulary(
    LanguageCode = 'en-US',
    VocabularyName = vocab_name,
    Phrases = [
        'CLI','Eva-Maria','ABCs'
    ]
)

while True:
    status = transcribe.get_vocabulary(VocabularyName = vocab_name)
    if status['VocabularyState'] in ['READY', 'FAILED']:
        break
    print("Not ready yet...")
    time.sleep(5)
print(status)

Note

If you create a new Amazon S3 bucket for your custom vocabulary files, make sure the IAM role making the CreateVocabulary request has permissions to access this bucket. If the role doesn't have the correct permissions, your request fails. You can optionally specify an IAM role within your request by including the DataAccessRoleArn parameter. For more information on IAM roles and policies in Amazon Transcribe, see Amazon Transcribe identity-based policy examples.