list-language-models¶

Description¶

Provides more information about the custom language models you’ve created. You can use the information in this list to find a specific custom language model. You can then use the operation to get more information about it.

Synopsis¶

  list-language-models
[--status-equals <value>]
[--name-contains <value>]
[--next-token <value>]
[--max-results <value>]
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]

Options¶

--status-equals (string)

When specified, returns only custom language models with the specified status. Language models are ordered by creation date, with the newest models first. If you don’t specify a status, Amazon Transcribe returns all custom language models ordered by date.

Possible values:

IN_PROGRESS

FAILED

COMPLETED

--name-contains (string)

When specified, the custom language model names returned contain the substring you’ve specified.

--next-token (string)

When included, fetches the next set of jobs if the result of the previous request was truncated.

--max-results (integer)

The maximum number of language models to return in the response. If there are fewer results in the list, the response contains only the actual results.

--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.

See ‘aws help’ for descriptions of global parameters.

Examples¶

To list your custom language models

The following list-language-models example lists the custom language models associated with your AWS account and Region. You can use the S3Uri and TuningDataS3Uri 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. The ModelStatus 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.

Output¶

NextToken -> (string)

The operation returns a page of jobs at a time. The maximum size of the list is set by the MaxResults parameter. If there are more language models in the list than the page size, Amazon Transcribe returns the NextPage token. Include the token in the next request to the operation to return the next page of language models.

Models -> (list)

A list of objects containing information about custom language models.

(structure)

The structure used to describe a custom language model.

ModelName -> (string)

The name of the custom language model.

CreateTime -> (timestamp)

The time the custom language model was created.

LastModifiedTime -> (timestamp)

The most recent time the custom language model was modified.

LanguageCode -> (string)

The language code you used to create your custom language model.

BaseModelName -> (string)

The Amazon Transcribe standard language model, or base model used to create the custom language model.

ModelStatus -> (string)

The creation status of a custom language model. When the status is COMPLETED the model is ready for use.

UpgradeAvailability -> (boolean)

Whether the base model used for the custom language model is up to date. If this field is true then you are running the most up-to-date version of the base model in your custom language model.

FailureReason -> (string)

The reason why the custom language model couldn’t be created.

InputDataConfig -> (structure)

The data access role and Amazon S3 prefixes for the input files used to train the custom language model.

S3Uri -> (string)

The Amazon S3 prefix you specify to access the plain text files that you use to train your custom language model.

TuningDataS3Uri -> (string)

The Amazon S3 prefix you specify to access the plain text files that you use to tune your custom language model.

DataAccessRoleArn -> (string)

The Amazon Resource Name (ARN) that uniquely identifies the permissions you’ve given Amazon Transcribe to access your Amazon S3 buckets containing your media files or text data.

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