Struct aws_sdk_transcribe::Client

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pub struct Client { /* private fields */ }

Expand description

Client for Amazon Transcribe Service

Client for invoking operations on Amazon Transcribe Service. Each operation on Amazon Transcribe Service is a method on this this struct. .send() MUST be invoked on the generated operations to dispatch the request to the service.

Examples

Constructing a client and invoking an operation

    // create a shared configuration. This can be used & shared between multiple service clients.
    let shared_config = aws_config::load_from_env().await;
    let client = aws_sdk_transcribe::Client::new(&shared_config);
    // invoke an operation
    /* let rsp = client
        .<operation_name>().
        .<param>("some value")
        .send().await; */

Constructing a client with custom configuration

use aws_config::RetryConfig;
let shared_config = aws_config::load_from_env().await;
let config = aws_sdk_transcribe::config::Builder::from(&shared_config)
  .retry_config(RetryConfig::disabled())
  .build();
let client = aws_sdk_transcribe::Client::from_conf(config);

Implementations

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impl Client

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pub fn with_config(
client: Client<DynConnector, DynMiddleware<DynConnector>>,
conf: Config
) -> Self

Creates a client with the given service configuration.

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pub fn conf(&self) -> &Config

Returns the client’s configuration.

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impl Client

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pub fn create_call_analytics_category(&self) -> CreateCallAnalyticsCategory

Constructs a fluent builder for the CreateCallAnalyticsCategory operation.

The fluent builder is configurable:
- category_name(impl Into<String>) / set_category_name(Option<String>):
 A unique name, chosen by you, for your call analytics category. For example, sentiment-positive-last30seconds.
- rules(Vec<Rule>) / set_rules(Option<Vec<Rule>>):
 Rules make up a call analytics category. When creating a call analytics category, you must create between 1 and 20 rules for your category. For each rule, you specify a filter you want applied to the attributes of a call. For example, you can choose a sentiment filter that detects if a customer’s sentiment was positive during the last 30 seconds of the call.
On success, responds with CreateCallAnalyticsCategoryOutput with field(s):
- category_properties(Option<CategoryProperties>):
 If your audio matches one of your categories, this field contains data on that category and its associated rules. This parameter shows which category is flagged (CategoryName) along with metadata for the rules that match your audio. Metadata includes the rule filter (such as InterruptionFilter, NonTalkTimeFilter, SentimentFilter, and TranscriptFilter) and where in your audio (StartTime and EndTime) the rule has a match.
On failure, responds with SdkError<CreateCallAnalyticsCategoryError>

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pub fn create_language_model(&self) -> CreateLanguageModel

Constructs a fluent builder for the CreateLanguageModel operation.

The fluent builder is configurable:
- language_code(ClmLanguageCode) / set_language_code(Option<ClmLanguageCode>):
 The language of your custom language model; note that the language code you select must match the language of your training and tuning data.
- base_model_name(BaseModelName) / set_base_model_name(Option<BaseModelName>):
 The Amazon Transcribe standard language model, or base model, used to create your custom language model. Amazon Transcribe offers two options for base models: Wideband and Narrowband.
 
 If the audio you want to transcribe has a sample rate of 16,000 Hz or greater, choose WideBand. To transcribe audio with a sample rate less than 16,000 Hz, choose NarrowBand.
- model_name(impl Into<String>) / set_model_name(Option<String>):
 The name of your new custom language model.
 
 This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account. If you try to create a language model with the same name as a previous language model, you get a ConflictException error.
- input_data_config(InputDataConfig) / set_input_data_config(Option<InputDataConfig>):
 Contains your data access role ARN (Amazon Resource Name) and the Amazon S3 locations of your training (S3Uri) and tuning (TuningDataS3Uri) data.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 Optionally add tags, each in the form of a key:value pair, to your new language model. See also: .
On success, responds with CreateLanguageModelOutput with field(s):
- language_code(Option<ClmLanguageCode>):
 The language code you selected for your custom language model.
- base_model_name(Option<BaseModelName>):
 The Amazon Transcribe standard language model, or base model, you used when creating your custom language model.
 
 If your audio has a sample rate of 16,000 Hz or greater, this value should be WideBand. If your audio has a sample rate of less than 16,000 Hz, this value should be NarrowBand.
- model_name(Option<String>):
 The unique name you chose for your custom language model.
- input_data_config(Option<InputDataConfig>):
 Lists your data access role ARN (Amazon Resource Name) and the Amazon S3 locations your provided for your training (S3Uri) and tuning (TuningDataS3Uri) data.
- model_status(Option<ModelStatus>):
 The status of your custom language model. When the status shows as COMPLETED, your model is ready to use.
On failure, responds with SdkError<CreateLanguageModelError>

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pub fn create_medical_vocabulary(&self) -> CreateMedicalVocabulary

Constructs a fluent builder for the CreateMedicalVocabulary operation.

The fluent builder is configurable:
- vocabulary_name(impl Into<String>) / set_vocabulary_name(Option<String>):
 The name of your new vocabulary.
 
 This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account. If you try to create a vocabulary with the same name as a previous vocabulary, you get a ConflictException error.
- language_code(LanguageCode) / set_language_code(Option<LanguageCode>):
 The language code that represents the language of the entries in your custom vocabulary. Note that U.S. English (en-US) is the only language supported with Amazon Transcribe Medical.
- vocabulary_file_uri(impl Into<String>) / set_vocabulary_file_uri(Option<String>):
 The Amazon S3 location (URI) of the text file that contains your custom vocabulary. The URI must be in the same Amazon Web Services Region as the resource that you’re calling.
 
 Here’s an example URI path:
 
 https://s3.us-east-1.amazonaws.com/my-s3-bucket/my-vocab-file.txt
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 Adds one or more tags, each in the form of a key:value pair, to a new medical vocabulary at the time you create the new vocabulary.
 
 To learn more about using tags with Amazon Transcribe, refer to Tagging resources.
On success, responds with CreateMedicalVocabularyOutput with field(s):
- vocabulary_name(Option<String>):
 The name you chose for your vocabulary.
- language_code(Option<LanguageCode>):
 The language code you selected for your medical vocabulary. Note that U.S. English (en-US) is the only language supported with Amazon Transcribe Medical.
- vocabulary_state(Option<VocabularyState>):
 The processing state of your custom medical vocabulary. If the state is READY, you can use the vocabulary in a StartMedicalTranscriptionJob request.
- last_modified_time(Option<DateTime>):
 The date and time you created your custom medical vocabulary.
- failure_reason(Option<String>):
 If the VocabularyState field is FAILED, FailureReason contains information about why the job failed.
On failure, responds with SdkError<CreateMedicalVocabularyError>

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pub fn create_vocabulary(&self) -> CreateVocabulary

Constructs a fluent builder for the CreateVocabulary operation.

The fluent builder is configurable:
- vocabulary_name(impl Into<String>) / set_vocabulary_name(Option<String>):
 The name of your new vocabulary.
 
 This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account. If you try to create a vocabulary with the same name as a previous vocabulary, you get a ConflictException error.
- language_code(LanguageCode) / set_language_code(Option<LanguageCode>):
 The language code that represents the language of the entries in your custom vocabulary. Each vocabulary must contain terms in only one language. For a list of languages and their corresponding language codes, see Supported languages.
- phrases(Vec<String>) / set_phrases(Option<Vec<String>>):
 Use this flag to include a list of terms within your request.
 
 Note that if you include Phrases in your request, you cannot use VocabularyFileUri; you must choose one or the other.
- vocabulary_file_uri(impl Into<String>) / set_vocabulary_file_uri(Option<String>):
 The S3 location of the text file that contains your custom vocabulary. The URI must be located in the same region as the API endpoint you’re calling.
 
 Here’s an example URI path:
 
 https://s3.us-east-1.amazonaws.com/my-s3-bucket/my-vocab-file.txt
 
 Note that if you include VocabularyFileUri in your request, you cannot use the Phrases flag; you must choose one or the other.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 Adds one or more tags, each in the form of a key:value pair, to a new custom vocabulary at the time you create this new vocabulary.
On success, responds with CreateVocabularyOutput with field(s):
- vocabulary_name(Option<String>):
 The name you chose for your vocabulary.
- language_code(Option<LanguageCode>):
 The language code you selected for your vocabulary.
- vocabulary_state(Option<VocabularyState>):
 The processing state of your vocabulary. If the state is READY, you can use the vocabulary in a StartTranscriptionJob request.
- last_modified_time(Option<DateTime>):
 The date and time you created your custom vocabulary.
- failure_reason(Option<String>):
 If the VocabularyState field is FAILED, FailureReason contains information about why the job failed.
On failure, responds with SdkError<CreateVocabularyError>

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pub fn create_vocabulary_filter(&self) -> CreateVocabularyFilter

Constructs a fluent builder for the CreateVocabularyFilter operation.

The fluent builder is configurable:
- vocabulary_filter_name(impl Into<String>) / set_vocabulary_filter_name(Option<String>):
 The name of your new vocabulary filter.
 
 This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account. If you try to create a vocabulary filter with the same name as a previous vocabulary filter, you get a ConflictException error.
- language_code(LanguageCode) / set_language_code(Option<LanguageCode>):
 The language code of the words in the vocabulary filter. All words in the filter must be in the same language. The vocabulary filter can only be used with transcription jobs in the specified language.
- words(Vec<String>) / set_words(Option<Vec<String>>):
 The words you want in your vocabulary filter. Only use characters specified in the Character sets for the language you’re transcribing.
 
 Note that if you include Words in your request, you cannot use VocabularyFilterFileUri; you must choose one or the other.
- vocabulary_filter_file_uri(impl Into<String>) / set_vocabulary_filter_file_uri(Option<String>):
 The Amazon S3 location of a text file used as input to create the vocabulary filter. Only use characters from the character set defined for custom vocabularies. For a list of character sets, see Character Sets for Custom Vocabularies.
 
 Your vocabulary filter file must be less than 50 KB in size.
 
 Note that if you include VocabularyFilterFileUri in your request, you cannot use Words; you must choose one or the other.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 Adds one or more tags, each in the form of a key:value pair, to a new vocabulary filter at the time you create this new vocabulary filter.
On success, responds with CreateVocabularyFilterOutput with field(s):
- vocabulary_filter_name(Option<String>):
 The name of the vocabulary filter.
- language_code(Option<LanguageCode>):
 The language code associated with your vocabulary filter.
- last_modified_time(Option<DateTime>):
 The date and time the vocabulary filter was modified.
On failure, responds with SdkError<CreateVocabularyFilterError>

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pub fn delete_call_analytics_category(&self) -> DeleteCallAnalyticsCategory

Constructs a fluent builder for the DeleteCallAnalyticsCategory operation.

The fluent builder is configurable:
- category_name(impl Into<String>) / set_category_name(Option<String>):
 The name of the call analytics category you want to delete. Category names are case-sensitive.
On success, responds with DeleteCallAnalyticsCategoryOutput
On failure, responds with SdkError<DeleteCallAnalyticsCategoryError>

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pub fn delete_call_analytics_job(&self) -> DeleteCallAnalyticsJob

Constructs a fluent builder for the DeleteCallAnalyticsJob operation.

The fluent builder is configurable:
- call_analytics_job_name(impl Into<String>) / set_call_analytics_job_name(Option<String>):
 The name of the call analytics job you want to delete. Job names are case-sensitive.
On success, responds with DeleteCallAnalyticsJobOutput
On failure, responds with SdkError<DeleteCallAnalyticsJobError>

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pub fn delete_language_model(&self) -> DeleteLanguageModel

Constructs a fluent builder for the DeleteLanguageModel operation.

The fluent builder is configurable:
- model_name(impl Into<String>) / set_model_name(Option<String>):
 The name of the model you want to delete. Model names are case-sensitive.
On success, responds with DeleteLanguageModelOutput
On failure, responds with SdkError<DeleteLanguageModelError>

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pub fn delete_medical_transcription_job(&self) -> DeleteMedicalTranscriptionJob

Constructs a fluent builder for the DeleteMedicalTranscriptionJob operation.

The fluent builder is configurable:
- medical_transcription_job_name(impl Into<String>) / set_medical_transcription_job_name(Option<String>):
 The name of the medical transcription job you want to delete. Job names are case-sensitive.
On success, responds with DeleteMedicalTranscriptionJobOutput
On failure, responds with SdkError<DeleteMedicalTranscriptionJobError>

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pub fn delete_medical_vocabulary(&self) -> DeleteMedicalVocabulary

Constructs a fluent builder for the DeleteMedicalVocabulary operation.

The fluent builder is configurable:
- vocabulary_name(impl Into<String>) / set_vocabulary_name(Option<String>):
 The name of the vocabulary that you want to delete. Vocabulary names are case-sensitive.
On success, responds with DeleteMedicalVocabularyOutput
On failure, responds with SdkError<DeleteMedicalVocabularyError>

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pub fn delete_transcription_job(&self) -> DeleteTranscriptionJob

Constructs a fluent builder for the DeleteTranscriptionJob operation.

The fluent builder is configurable:
- transcription_job_name(impl Into<String>) / set_transcription_job_name(Option<String>):
 The name of the transcription job you want to delete. Job names are case-sensitive.
On success, responds with DeleteTranscriptionJobOutput
On failure, responds with SdkError<DeleteTranscriptionJobError>

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pub fn delete_vocabulary(&self) -> DeleteVocabulary

Constructs a fluent builder for the DeleteVocabulary operation.

The fluent builder is configurable:
- vocabulary_name(impl Into<String>) / set_vocabulary_name(Option<String>):
 The name of the vocabulary you want to delete. Vocabulary names are case-sensitive.
On success, responds with DeleteVocabularyOutput
On failure, responds with SdkError<DeleteVocabularyError>

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pub fn delete_vocabulary_filter(&self) -> DeleteVocabularyFilter

Constructs a fluent builder for the DeleteVocabularyFilter operation.

The fluent builder is configurable:
- vocabulary_filter_name(impl Into<String>) / set_vocabulary_filter_name(Option<String>):
 The name of the vocabulary filter you want to delete. Vocabulary filter names are case-sensitive.
On success, responds with DeleteVocabularyFilterOutput
On failure, responds with SdkError<DeleteVocabularyFilterError>

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pub fn describe_language_model(&self) -> DescribeLanguageModel

Constructs a fluent builder for the DescribeLanguageModel operation.

The fluent builder is configurable:
- model_name(impl Into<String>) / set_model_name(Option<String>):
 The name of the custom language model you want described. Model names are case-sensitive.
On success, responds with DescribeLanguageModelOutput with field(s):
- language_model(Option<LanguageModel>):
 The name of the custom language model you requested more information about.
On failure, responds with SdkError<DescribeLanguageModelError>

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pub fn get_call_analytics_category(&self) -> GetCallAnalyticsCategory

Constructs a fluent builder for the GetCallAnalyticsCategory operation.

The fluent builder is configurable:
- category_name(impl Into<String>) / set_category_name(Option<String>):
 The name of the category you want information about. Category names are case sensitive.
On success, responds with GetCallAnalyticsCategoryOutput with field(s):
- category_properties(Option<CategoryProperties>):
 Provides you with the rules associated with the category you specified in your GetCallAnalyticsCategory request.
On failure, responds with SdkError<GetCallAnalyticsCategoryError>

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pub fn get_call_analytics_job(&self) -> GetCallAnalyticsJob

Constructs a fluent builder for the GetCallAnalyticsJob operation.

The fluent builder is configurable:
- call_analytics_job_name(impl Into<String>) / set_call_analytics_job_name(Option<String>):
 The name of the analytics job you want information about. This value is case sensitive.
On success, responds with GetCallAnalyticsJobOutput with field(s):
- call_analytics_job(Option<CallAnalyticsJob>):
 An object that contains detailed information about your call analytics job. Returned fields include: CallAnalyticsJobName, CallAnalyticsJobStatus, ChannelDefinitions, CompletionTime, CreationTime, DataAccessRoleArn, FailureReason, IdentifiedLanguageScore, LanguageCode, Media, MediaFormat, MediaSampleRateHertz, Settings, StartTime, and Transcript.
On failure, responds with SdkError<GetCallAnalyticsJobError>

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pub fn get_medical_transcription_job(&self) -> GetMedicalTranscriptionJob

Constructs a fluent builder for the GetMedicalTranscriptionJob operation.

The fluent builder is configurable:
- medical_transcription_job_name(impl Into<String>) / set_medical_transcription_job_name(Option<String>):
 The name of the medical transcription job you want information about. This value is case sensitive.
On success, responds with GetMedicalTranscriptionJobOutput with field(s):
- medical_transcription_job(Option<MedicalTranscriptionJob>):
 An object that contains detailed information about your medical transcription job. Returned fields include: CompletionTime, ContentIdentificationType, CreationTime, FailureReason, LanguageCode, Media, MediaFormat, MediaSampleRateHertz, MedicalTranscriptionJobName, Settings, Specialty, StartTime, Tags, Transcript, TranscriptionJobStatus, and Type.
On failure, responds with SdkError<GetMedicalTranscriptionJobError>

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pub fn get_medical_vocabulary(&self) -> GetMedicalVocabulary

Constructs a fluent builder for the GetMedicalVocabulary operation.

The fluent builder is configurable:
- vocabulary_name(impl Into<String>) / set_vocabulary_name(Option<String>):
 The name of the medical vocabulary you want information about. This value is case sensitive.
On success, responds with GetMedicalVocabularyOutput with field(s):
- vocabulary_name(Option<String>):
 The name of the vocabulary returned by Amazon Transcribe Medical.
- language_code(Option<LanguageCode>):
 The valid language code for your vocabulary entries.
- vocabulary_state(Option<VocabularyState>):
 The processing state of the vocabulary. If the VocabularyState is READY then you can use it in the StartMedicalTranscriptionJob operation.
- last_modified_time(Option<DateTime>):
 The date and time that the vocabulary was last modified with a text file different from the one that was previously used.
- failure_reason(Option<String>):
 If your request returns a VocabularyState that is FAILED, the FailureReason field contains information about why the request failed.
 
 For more information, refer to the Common Errors section.
- download_uri(Option<String>):
 The S3 location where the vocabulary is stored; use this URI to view or download the vocabulary.
On failure, responds with SdkError<GetMedicalVocabularyError>

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pub fn get_transcription_job(&self) -> GetTranscriptionJob

Constructs a fluent builder for the GetTranscriptionJob operation.

The fluent builder is configurable:
- transcription_job_name(impl Into<String>) / set_transcription_job_name(Option<String>):
 The name of the job.
On success, responds with GetTranscriptionJobOutput with field(s):
- transcription_job(Option<TranscriptionJob>):
 An object that contains the results of the transcription job.
On failure, responds with SdkError<GetTranscriptionJobError>

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pub fn get_vocabulary(&self) -> GetVocabulary

Constructs a fluent builder for the GetVocabulary operation.

The fluent builder is configurable:
- vocabulary_name(impl Into<String>) / set_vocabulary_name(Option<String>):
 The name of the vocabulary to return information about. The name is case sensitive.
On success, responds with GetVocabularyOutput with field(s):
- vocabulary_name(Option<String>):
 The name of the vocabulary to return.
- language_code(Option<LanguageCode>):
 The language code of the vocabulary entries.
- vocabulary_state(Option<VocabularyState>):
 The processing state of the vocabulary.
- last_modified_time(Option<DateTime>):
 The date and time that the vocabulary was last modified.
- failure_reason(Option<String>):
 If the VocabularyState field is FAILED, this field contains information about why the job failed.
- download_uri(Option<String>):
 The S3 location where the vocabulary is stored. Use this URI to get the contents of the vocabulary. The URI is available for a limited time.
On failure, responds with SdkError<GetVocabularyError>

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pub fn get_vocabulary_filter(&self) -> GetVocabularyFilter

Constructs a fluent builder for the GetVocabularyFilter operation.

The fluent builder is configurable:
- vocabulary_filter_name(impl Into<String>) / set_vocabulary_filter_name(Option<String>):
 The name of the vocabulary filter for which to return information.
On success, responds with GetVocabularyFilterOutput with field(s):
- vocabulary_filter_name(Option<String>):
 The name of the vocabulary filter.
- language_code(Option<LanguageCode>):
 The language code of the words in the vocabulary filter.
- last_modified_time(Option<DateTime>):
 The date and time that the contents of the vocabulary filter were updated.
- download_uri(Option<String>):
 The URI of the list of words in the vocabulary filter. You can use this URI to get the list of words.
On failure, responds with SdkError<GetVocabularyFilterError>

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pub fn list_call_analytics_categories(&self) -> ListCallAnalyticsCategories

Constructs a fluent builder for the ListCallAnalyticsCategories operation. This operation supports pagination; See into_paginator().

The fluent builder is configurable:
- next_token(impl Into<String>) / set_next_token(Option<String>):
 When included, NextTokenfetches the next set of categories if the result of the previous request was truncated.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of categories to return in each page of results. If there are fewer results than the value you specify, only the actual results are returned. If you do not specify a value, the default of 5 is used.
On success, responds with ListCallAnalyticsCategoriesOutput with field(s):
- next_token(Option<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 categories 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 analytics categories.
- categories(Option<Vec<CategoryProperties>>):
 A list of objects containing information about analytics categories.
On failure, responds with SdkError<ListCallAnalyticsCategoriesError>

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pub fn list_call_analytics_jobs(&self) -> ListCallAnalyticsJobs

Constructs a fluent builder for the ListCallAnalyticsJobs operation. This operation supports pagination; See into_paginator().

The fluent builder is configurable:
- status(CallAnalyticsJobStatus) / set_status(Option<CallAnalyticsJobStatus>):
 When specified, returns only call analytics jobs with the specified status. Jobs are ordered by creation date, with the most recent jobs returned first. If you don’t specify a status, Amazon Transcribe returns all analytics jobs ordered by creation date.
- job_name_contains(impl Into<String>) / set_job_name_contains(Option<String>):
 When specified, the jobs returned in the list are limited to jobs whose name contains the specified string.
- next_token(impl Into<String>) / set_next_token(Option<String>):
 If you receive a truncated result in the previous request of , include NextToken to fetch the next set of jobs.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of call analytics jobs to return in each page of results. If there are fewer results than the value you specify, only the actual results are returned. If you do not specify a value, the default of 5 is used.
On success, responds with ListCallAnalyticsJobsOutput with field(s):
- status(Option<CallAnalyticsJobStatus>):
 When specified, returns only call analytics jobs with that status. Jobs are ordered by creation date, with the most recent jobs returned first. If you don’t specify a status, Amazon Transcribe returns all transcription jobs ordered by creation date.
- next_token(Option<String>):
 The operation returns a page of jobs at a time. The maximum size of the page is set by the MaxResults parameter. If there are more jobs in the list than the page size, Amazon Transcribe returns the NextPage token. Include the token in your next request to the operation to return next page of jobs.
- call_analytics_job_summaries(Option<Vec<CallAnalyticsJobSummary>>):
 A list of objects containing summary information for a transcription job.
On failure, responds with SdkError<ListCallAnalyticsJobsError>

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pub fn list_language_models(&self) -> ListLanguageModels

Constructs a fluent builder for the ListLanguageModels operation. This operation supports pagination; See into_paginator().

The fluent builder is configurable:
- status_equals(ModelStatus) / set_status_equals(Option<ModelStatus>):
 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.
- name_contains(impl Into<String>) / set_name_contains(Option<String>):
 When specified, the custom language model names returned contain the substring you’ve specified.
- next_token(impl Into<String>) / set_next_token(Option<String>):
 When included, fetches the next set of jobs if the result of the previous request was truncated.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of language models to return in each page of results. If there are fewer results than the value you specify, only the actual results are returned. If you do not specify a value, the default of 5 is used.
On success, responds with ListLanguageModelsOutput with field(s):
- next_token(Option<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(Option<Vec<LanguageModel>>):
 A list of objects containing information about custom language models.
On failure, responds with SdkError<ListLanguageModelsError>

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pub fn list_medical_transcription_jobs(&self) -> ListMedicalTranscriptionJobs

Constructs a fluent builder for the ListMedicalTranscriptionJobs operation. This operation supports pagination; See into_paginator().

The fluent builder is configurable:
- status(TranscriptionJobStatus) / set_status(Option<TranscriptionJobStatus>):
 When specified, returns only medical transcription jobs with the specified status. Jobs are ordered by creation date, with the newest jobs returned first. If you don’t specify a status, Amazon Transcribe Medical returns all transcription jobs ordered by creation date.
- job_name_contains(impl Into<String>) / set_job_name_contains(Option<String>):
 When specified, the jobs returned in the list are limited to jobs whose name contains the specified string.
- next_token(impl Into<String>) / set_next_token(Option<String>):
 If you a receive a truncated result in the previous request of ListMedicalTranscriptionJobs, include NextToken to fetch the next set of jobs.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of medical transcription jobs to return in each page of results. If there are fewer results than the value you specify, only the actual results are returned. If you do not specify a value, the default of 5 is used.
On success, responds with ListMedicalTranscriptionJobsOutput with field(s):
- status(Option<TranscriptionJobStatus>):
 The requested status of the medical transcription jobs returned.
- next_token(Option<String>):
 The ListMedicalTranscriptionJobs operation returns a page of jobs at a time. The maximum size of the page is set by the MaxResults parameter. If the number of jobs exceeds what can fit on a page, Amazon Transcribe Medical returns the NextPage token. Include the token in the next request to the ListMedicalTranscriptionJobs operation to return in the next page of jobs.
- medical_transcription_job_summaries(Option<Vec<MedicalTranscriptionJobSummary>>):
 A list of objects containing summary information for a transcription job.
On failure, responds with SdkError<ListMedicalTranscriptionJobsError>

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pub fn list_medical_vocabularies(&self) -> ListMedicalVocabularies

Constructs a fluent builder for the ListMedicalVocabularies operation. This operation supports pagination; See into_paginator().

The fluent builder is configurable:
- next_token(impl Into<String>) / set_next_token(Option<String>):
 If the result of your previous request to ListMedicalVocabularies was truncated, include the NextToken to fetch the next set of vocabularies.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of vocabularies to return in each page of results. If there are fewer results than the value you specify, only the actual results are returned. If you do not specify a value, the default of 5 is used.
- state_equals(VocabularyState) / set_state_equals(Option<VocabularyState>):
 When specified, returns only vocabularies with the VocabularyState equal to the specified vocabulary state. Use this field to see which vocabularies are ready for your medical transcription jobs.
- name_contains(impl Into<String>) / set_name_contains(Option<String>):
 Returns vocabularies whose names contain the specified string. The search is not case sensitive. ListMedicalVocabularies returns both “vocabularyname” and “VocabularyName”.
On success, responds with ListMedicalVocabulariesOutput with field(s):
- status(Option<VocabularyState>):
 The requested vocabulary state.
- next_token(Option<String>):
 The ListMedicalVocabularies operation returns a page of vocabularies at a time. You set the maximum number of vocabularies to return on a page with the MaxResults parameter. If there are more jobs in the list will fit on a page, Amazon Transcribe Medical returns the NextPage token. To return the next page of vocabularies, include the token in the next request to the ListMedicalVocabularies operation.
- vocabularies(Option<Vec<VocabularyInfo>>):
 A list of objects that describe the vocabularies that match your search criteria.
On failure, responds with SdkError<ListMedicalVocabulariesError>

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pub fn list_tags_for_resource(&self) -> ListTagsForResource

Constructs a fluent builder for the ListTagsForResource operation.

The fluent builder is configurable:
- resource_arn(impl Into<String>) / set_resource_arn(Option<String>):
 Lists all tags associated with a given Amazon Resource Name (ARN). ARNs have the format arn:partition:service:region:account-id:resource-type/resource-id (for example, arn:aws:transcribe:us-east-1:account-id:transcription-job/your-job-name). Valid values for resource-type are: transcription-job, medical-transcription-job, vocabulary, medical-vocabulary, vocabulary-filter, and language-model.
On success, responds with ListTagsForResourceOutput with field(s):
- resource_arn(Option<String>):
 Lists all tags associated with the given Amazon Resource Name (ARN).
- tags(Option<Vec<Tag>>):
 Lists all tags associated with the given transcription job, vocabulary, or resource.
On failure, responds with SdkError<ListTagsForResourceError>

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pub fn list_transcription_jobs(&self) -> ListTranscriptionJobs

Constructs a fluent builder for the ListTranscriptionJobs operation. This operation supports pagination; See into_paginator().

The fluent builder is configurable:
- status(TranscriptionJobStatus) / set_status(Option<TranscriptionJobStatus>):
 When specified, returns only transcription jobs with the specified status. Jobs are ordered by creation date, with the newest jobs returned first. If you don’t specify a status, Amazon Transcribe returns all transcription jobs ordered by creation date.
- job_name_contains(impl Into<String>) / set_job_name_contains(Option<String>):
 When specified, the jobs returned in the list are limited to jobs whose name contains the specified string.
- next_token(impl Into<String>) / set_next_token(Option<String>):
 If the result of the previous request to ListTranscriptionJobs is truncated, include the NextToken to fetch the next set of jobs.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of jobs to return in each page of results. If there are fewer results than the value you specify, only the actual results are returned. If you do not specify a value, the default of 5 is used.
On success, responds with ListTranscriptionJobsOutput with field(s):
- status(Option<TranscriptionJobStatus>):
 The requested status of the jobs returned.
- next_token(Option<String>):
 The ListTranscriptionJobs operation returns a page of jobs at a time. The maximum size of the page is set by the MaxResults parameter. If there are more jobs in the list than the page size, Amazon Transcribe returns the NextPage token. Include the token in the next request to the ListTranscriptionJobs operation to return in the next page of jobs.
- transcription_job_summaries(Option<Vec<TranscriptionJobSummary>>):
 A list of objects containing summary information for a transcription job.
On failure, responds with SdkError<ListTranscriptionJobsError>

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pub fn list_vocabularies(&self) -> ListVocabularies

Constructs a fluent builder for the ListVocabularies operation. This operation supports pagination; See into_paginator().

The fluent builder is configurable:
- next_token(impl Into<String>) / set_next_token(Option<String>):
 If the result of the previous request to ListVocabularies was truncated, include the NextToken to fetch the next set of jobs.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of vocabularies to return in each page of results. If there are fewer results than the value you specify, only the actual results are returned. If you do not specify a value, the default of 5 is used.
- state_equals(VocabularyState) / set_state_equals(Option<VocabularyState>):
 When specified, only returns vocabularies with the VocabularyState field equal to the specified state.
- name_contains(impl Into<String>) / set_name_contains(Option<String>):
 When specified, the vocabularies returned in the list are limited to vocabularies whose name contains the specified string. The search is not case sensitive, ListVocabularies returns both “vocabularyname” and “VocabularyName” in the response list.
On success, responds with ListVocabulariesOutput with field(s):
- status(Option<VocabularyState>):
 The requested vocabulary state.
- next_token(Option<String>):
 The ListVocabularies operation returns a page of vocabularies at a time. The maximum size of the page is set in the MaxResults parameter. If there are more jobs in the list than will fit on the page, Amazon Transcribe returns the NextPage token. To return in the next page of jobs, include the token in the next request to the ListVocabularies operation.
- vocabularies(Option<Vec<VocabularyInfo>>):
 A list of objects that describe the vocabularies that match the search criteria in the request.
On failure, responds with SdkError<ListVocabulariesError>

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pub fn list_vocabulary_filters(&self) -> ListVocabularyFilters

Constructs a fluent builder for the ListVocabularyFilters operation. This operation supports pagination; See into_paginator().

The fluent builder is configurable:
- next_token(impl Into<String>) / set_next_token(Option<String>):
 If the result of the previous request to ListVocabularyFilters was truncated, include the NextToken to fetch the next set of collections.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of filters to return in each page of results. If there are fewer results than the value you specify, only the actual results are returned. If you do not specify a value, the default of 5 is used.
- name_contains(impl Into<String>) / set_name_contains(Option<String>):
 Filters the response so that it only contains vocabulary filters whose name contains the specified string.
On success, responds with ListVocabularyFiltersOutput with field(s):
- next_token(Option<String>):
 The ListVocabularyFilters operation returns a page of collections at a time. The maximum size of the page is set by the MaxResults parameter. If there are more jobs in the list than the page size, Amazon Transcribe returns the NextPage token. Include the token in the next request to the ListVocabularyFilters operation to return in the next page of jobs.
- vocabulary_filters(Option<Vec<VocabularyFilterInfo>>):
 The list of vocabulary filters. It contains at most MaxResults number of filters. If there are more filters, call the ListVocabularyFilters operation again with the NextToken parameter in the request set to the value of the NextToken field in the response.
On failure, responds with SdkError<ListVocabularyFiltersError>

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pub fn start_call_analytics_job(&self) -> StartCallAnalyticsJob

Constructs a fluent builder for the StartCallAnalyticsJob operation.

The fluent builder is configurable:
- call_analytics_job_name(impl Into<String>) / set_call_analytics_job_name(Option<String>):
 The name of the call analytics job. You can’t use the string “.” or “..” by themselves as the job name. The name must also be unique within an Amazon Web Services account. If you try to create a call analytics job with the same name as a previous call analytics job, you get a ConflictException error.
- media(Media) / set_media(Option<Media>):
 Describes the input media file in a transcription request.
- output_location(impl Into<String>) / set_output_location(Option<String>):
 The Amazon S3 location where the output of the call analytics job is stored. You can provide the following location types to store the output of call analytics job:
 - s3://DOC-EXAMPLE-BUCKET1
 
 If you specify a bucket, Amazon Transcribe saves the output of the analytics job as a JSON file at the root level of the bucket.
 - s3://DOC-EXAMPLE-BUCKET1/folder/
 
 f you specify a path, Amazon Transcribe saves the output of the analytics job as s3://DOC-EXAMPLE-BUCKET1/folder/your-transcription-job-name.json.
 
 If you specify a folder, you must provide a trailing slash.
 - s3://DOC-EXAMPLE-BUCKET1/folder/filename.json.
 
 If you provide a path that has the filename specified, Amazon Transcribe saves the output of the analytics job as s3://DOC-EXAMPLEBUCKET1/folder/filename.json.
 You can specify an Amazon Web Services Key Management Service (KMS) key to encrypt the output of our analytics job using the OutputEncryptionKMSKeyId parameter. If you don’t specify a KMS key, Amazon Transcribe uses the default Amazon S3 key for server-side encryption of the analytics job output that is placed in your S3 bucket.
- output_encryption_kms_key_id(impl Into<String>) / set_output_encryption_kms_key_id(Option<String>):
 The Amazon Resource Name (ARN) of the Amazon Web Services Key Management Service key used to encrypt the output of the call analytics job. The user calling the operation must have permission to use the specified KMS key.
 
 You use either of the following to identify an Amazon Web Services KMS key in the current account:
 - KMS Key ID: “1234abcd-12ab-34cd-56ef-1234567890ab”
 - KMS Key Alias: “alias/ExampleAlias”
 You can use either of the following to identify a KMS key in the current account or another account:
 - Amazon Resource Name (ARN) of a KMS key in the current account or another account: “arn:aws:kms:region:account ID:key/1234abcd-12ab-34cd-56ef1234567890ab”
 - ARN of a KMS Key Alias: “arn:aws:kms:region:accountID:alias/ExampleAlias”
 If you don’t specify an encryption key, the output of the call analytics job is encrypted with the default Amazon S3 key (SSE-S3).
 
 If you specify a KMS key to encrypt your output, you must also specify an output location in the OutputLocation parameter.
- data_access_role_arn(impl Into<String>) / set_data_access_role_arn(Option<String>):
 The Amazon Resource Name (ARN) of a role that has access to the S3 bucket that contains your input files. Amazon Transcribe assumes this role to read queued audio files. If you have specified an output S3 bucket for your transcription results, this role should have access to the output bucket as well.
- settings(CallAnalyticsJobSettings) / set_settings(Option<CallAnalyticsJobSettings>):
 A Settings object that provides optional settings for a call analytics job.
- channel_definitions(Vec<ChannelDefinition>) / set_channel_definitions(Option<Vec<ChannelDefinition>>):
 When you start a call analytics job, you must pass an array that maps the agent and the customer to specific audio channels. The values you can assign to a channel are 0 and 1. The agent and the customer must each have their own channel. You can’t assign more than one channel to an agent or customer.
On success, responds with StartCallAnalyticsJobOutput with field(s):
- call_analytics_job(Option<CallAnalyticsJob>):
 An object containing the details of the asynchronous call analytics job.
On failure, responds with SdkError<StartCallAnalyticsJobError>

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pub fn start_medical_transcription_job(&self) -> StartMedicalTranscriptionJob

Constructs a fluent builder for the StartMedicalTranscriptionJob operation.

The fluent builder is configurable:
- medical_transcription_job_name(impl Into<String>) / set_medical_transcription_job_name(Option<String>):
 The name of the medical transcription job. You can’t use the strings “.” or “..” by themselves as the job name. The name must also be unique within an Amazon Web Services account. If you try to create a medical transcription job with the same name as a previous medical transcription job, you get a ConflictException error.
- language_code(LanguageCode) / set_language_code(Option<LanguageCode>):
 The language code for the language spoken in the input media file. US English (en-US) is the valid value for medical transcription jobs. Any other value you enter for language code results in a BadRequestException error.
- media_sample_rate_hertz(i32) / set_media_sample_rate_hertz(Option<i32>):
 The sample rate, in Hertz, of the audio track in the input media file.
 
 If you do not specify the media sample rate, Amazon Transcribe Medical determines the sample rate. If you specify the sample rate, it must match the rate detected by Amazon Transcribe Medical. In most cases, you should leave the MediaSampleRateHertz field blank and let Amazon Transcribe Medical determine the sample rate.
- media_format(MediaFormat) / set_media_format(Option<MediaFormat>):
 The audio format of the input media file.
- media(Media) / set_media(Option<Media>):
 Describes the input media file in a transcription request.
- output_bucket_name(impl Into<String>) / set_output_bucket_name(Option<String>):
 The Amazon S3 location where the transcription is stored.
 
 You must set OutputBucketName for Amazon Transcribe Medical to store the transcription results. Your transcript appears in the S3 location you specify. When you call the GetMedicalTranscriptionJob, the operation returns this location in the TranscriptFileUri field. The S3 bucket must have permissions that allow Amazon Transcribe Medical to put files in the bucket. For more information, see Permissions Required for IAM User Roles.
 
 You can specify an Amazon Web Services Key Management Service (KMS) key to encrypt the output of your transcription using the OutputEncryptionKMSKeyId parameter. If you don’t specify a KMS key, Amazon Transcribe Medical uses the default Amazon S3 key for server-side encryption of transcripts that are placed in your S3 bucket.
- output_key(impl Into<String>) / set_output_key(Option<String>):
 You can specify a location in an Amazon S3 bucket to store the output of your medical transcription job.
 
 If you don’t specify an output key, Amazon Transcribe Medical stores the output of your transcription job in the Amazon S3 bucket you specified. By default, the object key is “your-transcription-job-name.json”.
 
 You can use output keys to specify the Amazon S3 prefix and file name of the transcription output. For example, specifying the Amazon S3 prefix, “folder1/folder2/”, as an output key would lead to the output being stored as “folder1/folder2/your-transcription-job-name.json”. If you specify “my-other-job-name.json” as the output key, the object key is changed to “my-other-job-name.json”. You can use an output key to change both the prefix and the file name, for example “folder/my-other-job-name.json”.
 
 If you specify an output key, you must also specify an S3 bucket in the OutputBucketName parameter.
- output_encryption_kms_key_id(impl Into<String>) / set_output_encryption_kms_key_id(Option<String>):
 The Amazon Resource Name (ARN) of the Amazon Web Services Key Management Service (KMS) key used to encrypt the output of the transcription job. The user calling the StartMedicalTranscriptionJob operation must have permission to use the specified KMS key.
 
 You use either of the following to identify a KMS key in the current account:
 - KMS Key ID: “1234abcd-12ab-34cd-56ef-1234567890ab”
 - KMS Key Alias: “alias/ExampleAlias”
 You can use either of the following to identify a KMS key in the current account or another account:
 - Amazon Resource Name (ARN) of a KMS key in the current account or another account: “arn:aws:kms:region:account-ID:key/1234abcd-12ab-34cd-56ef-1234567890ab”
 - ARN of a KMS Key Alias: “arn:aws:kms:region:account ID:alias/ExampleAlias”
 If you don’t specify an encryption key, the output of the medical transcription job is encrypted with the default Amazon S3 key (SSE-S3).
 
 If you specify a KMS key to encrypt your output, you must also specify an output location in the OutputBucketName parameter.
- kms_encryption_context(HashMap<String, String>) / set_kms_encryption_context(Option<HashMap<String, String>>):
 A map of plain text, non-secret key:value pairs, known as encryption context pairs, that provide an added layer of security for your data.
- settings(MedicalTranscriptionSetting) / set_settings(Option<MedicalTranscriptionSetting>):
 Optional settings for the medical transcription job.
- content_identification_type(MedicalContentIdentificationType) / set_content_identification_type(Option<MedicalContentIdentificationType>):
 You can configure Amazon Transcribe Medical to label content in the transcription output. If you specify PHI, Amazon Transcribe Medical labels the personal health information (PHI) that it identifies in the transcription output.
- specialty(Specialty) / set_specialty(Option<Specialty>):
 The medical specialty of any clinician speaking in the input media.
- r#type(Type) / set_type(Option<Type>):
 The type of speech in the input audio. CONVERSATION refers to conversations between two or more speakers, e.g., a conversations between doctors and patients. DICTATION refers to single-speaker dictated speech, such as clinical notes.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 Add tags to an Amazon Transcribe Medical transcription job.
On success, responds with StartMedicalTranscriptionJobOutput with field(s):
- medical_transcription_job(Option<MedicalTranscriptionJob>):
 A batch job submitted to transcribe medical speech to text.
On failure, responds with SdkError<StartMedicalTranscriptionJobError>

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pub fn start_transcription_job(&self) -> StartTranscriptionJob

Constructs a fluent builder for the StartTranscriptionJob operation.

The fluent builder is configurable:
- transcription_job_name(impl Into<String>) / set_transcription_job_name(Option<String>):
 The name of the job. You can’t use the strings “.” or “..” by themselves as the job name. The name must also be unique within an Amazon Web Services account. If you try to create a transcription job with the same name as a previous transcription job, you get a ConflictException error.
- language_code(LanguageCode) / set_language_code(Option<LanguageCode>):
 The language code for the language used in the input media file. You must include either LanguageCode or IdentifyLanguage in your request.
 
 To transcribe speech in Modern Standard Arabic (ar-SA), your audio or video file must be encoded at a sample rate of 16,000 Hz or higher.
- media_sample_rate_hertz(i32) / set_media_sample_rate_hertz(Option<i32>):
 The sample rate, in Hertz, of the audio track in the input media file.
 
 If you do not specify the media sample rate, Amazon Transcribe determines the sample rate. If you specify the sample rate, it must match the sample rate detected by Amazon Transcribe. In most cases, you should leave the MediaSampleRateHertz field blank and let Amazon Transcribe determine the sample rate.
- media_format(MediaFormat) / set_media_format(Option<MediaFormat>):
 The format of the input media file.
- media(Media) / set_media(Option<Media>):
 An object that describes the input media for a transcription job.
- output_bucket_name(impl Into<String>) / set_output_bucket_name(Option<String>):
 The location where the transcription is stored.
 
 If you set the OutputBucketName, Amazon Transcribe puts the transcript in the specified S3 bucket. When you call the GetTranscriptionJob operation, the operation returns this location in the TranscriptFileUri field. If you enable content redaction, the redacted transcript appears in RedactedTranscriptFileUri. If you enable content redaction and choose to output an unredacted transcript, that transcript’s location still appears in the TranscriptFileUri. The S3 bucket must have permissions that allow Amazon Transcribe to put files in the bucket. For more information, see Permissions Required for IAM User Roles.
 
 You can specify an Amazon Web Services Key Management Service (KMS) key to encrypt the output of your transcription using the OutputEncryptionKMSKeyId parameter. If you don’t specify a KMS key, Amazon Transcribe uses the default Amazon S3 key for server-side encryption of transcripts that are placed in your S3 bucket.
 
 If you don’t set the OutputBucketName, Amazon Transcribe generates a pre-signed URL, a shareable URL that provides secure access to your transcription, and returns it in the TranscriptFileUri field. Use this URL to download the transcription.
- output_key(impl Into<String>) / set_output_key(Option<String>):
 You can specify a location in an Amazon S3 bucket to store the output of your transcription job.
 
 If you don’t specify an output key, Amazon Transcribe stores the output of your transcription job in the Amazon S3 bucket you specified. By default, the object key is “your-transcription-job-name.json”.
 
 You can use output keys to specify the Amazon S3 prefix and file name of the transcription output. For example, specifying the Amazon S3 prefix, “folder1/folder2/”, as an output key would lead to the output being stored as “folder1/folder2/your-transcription-job-name.json”. If you specify “my-other-job-name.json” as the output key, the object key is changed to “my-other-job-name.json”. You can use an output key to change both the prefix and the file name, for example “folder/my-other-job-name.json”.
 
 If you specify an output key, you must also specify an S3 bucket in the OutputBucketName parameter.
- output_encryption_kms_key_id(impl Into<String>) / set_output_encryption_kms_key_id(Option<String>):
 The Amazon Resource Name (ARN) of the Amazon Web Services Key Management Service (KMS) key used to encrypt the output of the transcription job. The user calling the StartTranscriptionJob operation must have permission to use the specified KMS key.
 
 You can use either of the following to identify a KMS key in the current account:
 - KMS Key ID: “1234abcd-12ab-34cd-56ef-1234567890ab”
 - KMS Key Alias: “alias/ExampleAlias”
 You can use either of the following to identify a KMS key in the current account or another account:
 - Amazon Resource Name (ARN) of a KMS Key: “arn:aws:kms:region:account ID:key/1234abcd-12ab-34cd-56ef-1234567890ab”
 - ARN of a KMS Key Alias: “arn:aws:kms:region:account-ID:alias/ExampleAlias”
 If you don’t specify an encryption key, the output of the transcription job is encrypted with the default Amazon S3 key (SSE-S3).
 
 If you specify a KMS key to encrypt your output, you must also specify an output location in the OutputBucketName parameter.
- kms_encryption_context(HashMap<String, String>) / set_kms_encryption_context(Option<HashMap<String, String>>):
 A map of plain text, non-secret key:value pairs, known as encryption context pairs, that provide an added layer of security for your data.
- settings(Settings) / set_settings(Option<Settings>):
 A Settings object that provides optional settings for a transcription job.
- model_settings(ModelSettings) / set_model_settings(Option<ModelSettings>):
 Choose the custom language model you use for your transcription job in this parameter.
- job_execution_settings(JobExecutionSettings) / set_job_execution_settings(Option<JobExecutionSettings>):
 Provides information about how a transcription job is executed. Use this field to indicate that the job can be queued for deferred execution if the concurrency limit is reached and there are no slots available to immediately run the job.
- content_redaction(ContentRedaction) / set_content_redaction(Option<ContentRedaction>):
 An object that contains the request parameters for content redaction.
- identify_language(bool) / set_identify_language(Option<bool>):
 Set this field to true to enable automatic language identification. Automatic language identification is disabled by default. You receive a BadRequestException error if you enter a value for a LanguageCode.
 
 You must include either LanguageCode or IdentifyLanguage in your request.
- language_options(Vec<LanguageCode>) / set_language_options(Option<Vec<LanguageCode>>):
 An object containing a list of languages that might be present in your collection of audio files. Automatic language identification chooses a language that best matches the source audio from that list.
 
 To transcribe speech in Modern Standard Arabic (ar-SA), your audio or video file must be encoded at a sample rate of 16,000 Hz or higher.
- subtitles(Subtitles) / set_subtitles(Option<Subtitles>):
 Add subtitles to your batch transcription job.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 Add tags to an Amazon Transcribe transcription job.
- language_id_settings(HashMap<LanguageCode, LanguageIdSettings>) / set_language_id_settings(Option<HashMap<LanguageCode, LanguageIdSettings>>):
 The language identification settings associated with your transcription job. These settings include VocabularyName, VocabularyFilterName, and LanguageModelName.
On success, responds with StartTranscriptionJobOutput with field(s):
- transcription_job(Option<TranscriptionJob>):
 Provides information about your asynchronous transcription job.
On failure, responds with SdkError<StartTranscriptionJobError>

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pub fn tag_resource(&self) -> TagResource

Constructs a fluent builder for the TagResource operation.

The fluent builder is configurable:
- resource_arn(impl Into<String>) / set_resource_arn(Option<String>):
 The Amazon Resource Name (ARN) of the Amazon Transcribe resource you want to tag. ARNs have the format arn:partition:service:region:account-id:resource-type/resource-id (for example, arn:aws:transcribe:us-east-1:account-id:transcription-job/your-job-name). Valid values for resource-type are: transcription-job, medical-transcription-job, vocabulary, medical-vocabulary, vocabulary-filter, and language-model.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 The tags you are assigning to a given Amazon Transcribe resource.
On success, responds with TagResourceOutput
On failure, responds with SdkError<TagResourceError>

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pub fn untag_resource(&self) -> UntagResource

Constructs a fluent builder for the UntagResource operation.

The fluent builder is configurable:
- resource_arn(impl Into<String>) / set_resource_arn(Option<String>):
 The Amazon Resource Name (ARN) of the Amazon Transcribe resource you want to remove tags from. ARNs have the format arn:partition:service:region:account-id:resource-type/resource-id (for example, arn:aws:transcribe:us-east-1:account-id:transcription-job/your-job-name). Valid values for resource-type are: transcription-job, medical-transcription-job, vocabulary, medical-vocabulary, vocabulary-filter, and language-model.
- tag_keys(Vec<String>) / set_tag_keys(Option<Vec<String>>):
 A list of tag keys you want to remove from a specified Amazon Transcribe resource.
On success, responds with UntagResourceOutput
On failure, responds with SdkError<UntagResourceError>

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pub fn update_call_analytics_category(&self) -> UpdateCallAnalyticsCategory

Constructs a fluent builder for the UpdateCallAnalyticsCategory operation.

The fluent builder is configurable:
- category_name(impl Into<String>) / set_category_name(Option<String>):
 The name of the analytics category to update. The name is case sensitive. If you try to update a call analytics category with the same name as a previous category you will receive a ConflictException error.
- rules(Vec<Rule>) / set_rules(Option<Vec<Rule>>):
 The rules used for the updated analytics category. The rules that you provide in this field replace the ones that are currently being used.
On success, responds with UpdateCallAnalyticsCategoryOutput with field(s):
- category_properties(Option<CategoryProperties>):
 The attributes describing the analytics category. You can see information such as the rules that you’ve used to update the category and when the category was originally created.
On failure, responds with SdkError<UpdateCallAnalyticsCategoryError>

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pub fn update_medical_vocabulary(&self) -> UpdateMedicalVocabulary

Constructs a fluent builder for the UpdateMedicalVocabulary operation.

The fluent builder is configurable:
- vocabulary_name(impl Into<String>) / set_vocabulary_name(Option<String>):
 The name of the vocabulary to update. The name is case sensitive. If you try to update a vocabulary with the same name as a vocabulary you’ve already made, you get a ConflictException error.
- language_code(LanguageCode) / set_language_code(Option<LanguageCode>):
 The language code of the language used for the entries in the updated vocabulary. U.S. English (en-US) is the only valid language code in Amazon Transcribe Medical.
- vocabulary_file_uri(impl Into<String>) / set_vocabulary_file_uri(Option<String>):
 The location in Amazon S3 of the text file that contains your custom vocabulary. The URI must be in the same Amazon Web Services Region as the resource that you are calling. The following is the format for a URI:
 
 https://s3.aws-region.amazonaws.com/bucket-name/keyprefix/objectkey
 
 For example:
 
 https://s3.us-east-1.amazonaws.com/DOC-EXAMPLE-BUCKET/vocab.txt
 
 For more information about Amazon S3 object names, see Object Keys in the Amazon S3 Developer Guide.
 
 For more information about custom vocabularies in Amazon Transcribe Medical, see Medical Custom Vocabularies.
On success, responds with UpdateMedicalVocabularyOutput with field(s):
- vocabulary_name(Option<String>):
 The name of the updated vocabulary.
- language_code(Option<LanguageCode>):
 The language code for the language of the text file used to update the custom vocabulary. US English (en-US) is the only language supported in Amazon Transcribe Medical.
- last_modified_time(Option<DateTime>):
 The date and time that the vocabulary was updated.
- vocabulary_state(Option<VocabularyState>):
 The processing state of the update to the vocabulary. When the VocabularyState field is READY, the vocabulary is ready to be used in a StartMedicalTranscriptionJob request.
On failure, responds with SdkError<UpdateMedicalVocabularyError>

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pub fn update_vocabulary(&self) -> UpdateVocabulary

Constructs a fluent builder for the UpdateVocabulary operation.

The fluent builder is configurable:
- vocabulary_name(impl Into<String>) / set_vocabulary_name(Option<String>):
 The name of the vocabulary to update. The name is case sensitive. If you try to update a vocabulary with the same name as a previous vocabulary you will receive a ConflictException error.
- language_code(LanguageCode) / set_language_code(Option<LanguageCode>):
 The language code of the vocabulary entries. For a list of languages and their corresponding language codes, see Supported languages.
- phrases(Vec<String>) / set_phrases(Option<Vec<String>>):
 An array of strings containing the vocabulary entries.
- vocabulary_file_uri(impl Into<String>) / set_vocabulary_file_uri(Option<String>):
 The S3 location of the text file that contains the definition of the custom vocabulary. The URI must be in the same region as the API endpoint that you are calling. The general form is:
 
 https://s3.aws-region.amazonaws.com/bucket-name/keyprefix/objectkey
 
 For example:
 
 https://s3.us-east-1.amazonaws.com/DOC-EXAMPLE-BUCKET/vocab.txt
 
 For more information about S3 object names, see Object Keys in the Amazon S3 Developer Guide.
 
 For more information about custom vocabularies, see Custom Vocabularies.
On success, responds with UpdateVocabularyOutput with field(s):
- vocabulary_name(Option<String>):
 The name of the vocabulary that was updated.
- language_code(Option<LanguageCode>):
 The language code of the vocabulary entries.
- last_modified_time(Option<DateTime>):
 The date and time that the vocabulary was updated.
- vocabulary_state(Option<VocabularyState>):
 The processing state of the vocabulary. When the VocabularyState field contains READY the vocabulary is ready to be used in a StartTranscriptionJob request.
On failure, responds with SdkError<UpdateVocabularyError>

source

pub fn update_vocabulary_filter(&self) -> UpdateVocabularyFilter

Constructs a fluent builder for the UpdateVocabularyFilter operation.

The fluent builder is configurable:
- vocabulary_filter_name(impl Into<String>) / set_vocabulary_filter_name(Option<String>):
 The name of the vocabulary filter to update. If you try to update a vocabulary filter with the same name as another vocabulary filter, you get a ConflictException error.
- words(Vec<String>) / set_words(Option<Vec<String>>):
 The words to use in the vocabulary filter. Only use characters from the character set defined for custom vocabularies. For a list of character sets, see Character Sets for Custom Vocabularies.
 
 If you provide a list of words in the Words parameter, you can’t use the VocabularyFilterFileUri parameter.
- vocabulary_filter_file_uri(impl Into<String>) / set_vocabulary_filter_file_uri(Option<String>):
 The Amazon S3 location of a text file used as input to create the vocabulary filter. Only use characters from the character set defined for custom vocabularies. For a list of character sets, see Character Sets for Custom Vocabularies.
 
 The specified file must be less than 50 KB of UTF-8 characters.
 
 If you provide the location of a list of words in the VocabularyFilterFileUri parameter, you can’t use the Words parameter.
On success, responds with UpdateVocabularyFilterOutput with field(s):
- vocabulary_filter_name(Option<String>):
 The name of the updated vocabulary filter.
- language_code(Option<LanguageCode>):
 The language code of the words in the vocabulary filter.
- last_modified_time(Option<DateTime>):
 The date and time that the vocabulary filter was updated.
On failure, responds with SdkError<UpdateVocabularyFilterError>