describe-language-model¶

Description¶

Gets information about a single custom language model. Use this information to see details about the language model in your AWS account. You can also see whether the base language model used to create your custom language model has been updated. If Amazon Transcribe has updated the base model, you can create a new custom language model using the updated base model. If the language model wasn’t created, you can use this operation to understand why Amazon Transcribe couldn’t create it.

Synopsis¶

  describe-language-model
--model-name <value>
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]

Options¶

--model-name (string)

The name of the custom language model you submit to get more information.

--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 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.

Output¶

LanguageModel -> (structure)

The name of the custom language model you requested more information about.

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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