Create Vocabulary
connect_create_vocabulary | R Documentation |
Creates a custom vocabulary associated with your Amazon Connect instance¶
Description¶
Creates a custom vocabulary associated with your Amazon Connect instance. You can set a custom vocabulary to be your default vocabulary for a given language. Contact Lens for Amazon Connect uses the default vocabulary in post-call and real-time contact analysis sessions for that language.
Usage¶
Arguments¶
ClientToken
A unique, case-sensitive identifier that you provide to ensure the idempotency of the request. If not provided, the Amazon Web Services SDK populates this field. For more information about idempotency, see Making retries safe with idempotent APIs. If a create request is received more than once with same client token, subsequent requests return the previous response without creating a vocabulary again.
InstanceId
[required] The identifier of the Amazon Connect instance. You can find the instance ID in the Amazon Resource Name (ARN) of the instance.
VocabularyName
[required] A unique name of the custom vocabulary.
LanguageCode
[required] The language code of the vocabulary entries. For a list of languages and their corresponding language codes, see What is Amazon Transcribe?
Content
[required] The content of the custom vocabulary in plain-text format with a table of values. Each row in the table represents a word or a phrase, described with
Phrase
,IPA
,SoundsLike
, andDisplayAs
fields. Separate the fields with TAB characters. The size limit is 50KB. For more information, see Create a custom vocabulary using a table.Tags
The tags used to organize, track, or control access for this resource. For example, { "Tags": {"key1":"value1", "key2":"value2"} }.
Value¶
A list with the following syntax:
list(
VocabularyArn = "string",
VocabularyId = "string",
State = "CREATION_IN_PROGRESS"|"ACTIVE"|"CREATION_FAILED"|"DELETE_IN_PROGRESS"
)
Request syntax¶
svc$create_vocabulary(
ClientToken = "string",
InstanceId = "string",
VocabularyName = "string",
LanguageCode = "ar-AE"|"de-CH"|"de-DE"|"en-AB"|"en-AU"|"en-GB"|"en-IE"|"en-IN"|"en-US"|"en-WL"|"es-ES"|"es-US"|"fr-CA"|"fr-FR"|"hi-IN"|"it-IT"|"ja-JP"|"ko-KR"|"pt-BR"|"pt-PT"|"zh-CN"|"en-NZ"|"en-ZA",
Content = "string",
Tags = list(
"string"
)
)