# WARNING: DO NOT EDIT, AUTO-GENERATED CODE!
# See https://github.com/aws-beam/aws-codegen for more details.
defmodule AWS.Transcribe do
@moduledoc """
Amazon Transcribe offers three main types of batch transcription: **Standard**,
**Medical**, and
**Call Analytics**.
*
**Standard transcriptions** are the most common
option. Refer to for details.
*
**Medical transcriptions** are tailored to
medical professionals and incorporate medical terms. A common use case for this
service is transcribing doctor-patient dialogue into after-visit notes. Refer to
for details.
*
**Call Analytics transcriptions** are designed
for use with call center audio on two different channels; if you're looking for
insight into customer service calls, use this option. Refer to for details.
"""
alias AWS.Client
alias AWS.Request
@typedoc """
## Example:
list_vocabularies_response() :: %{
"NextToken" => String.t() | atom(),
"Status" => list(any()),
"Vocabularies" => list(vocabulary_info())
}
"""
@type list_vocabularies_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
get_transcription_job_response() :: %{
"TranscriptionJob" => transcription_job()
}
"""
@type get_transcription_job_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
call_analytics_job_summary() :: %{
"CallAnalyticsJobDetails" => call_analytics_job_details(),
"CallAnalyticsJobName" => String.t() | atom(),
"CallAnalyticsJobStatus" => list(any()),
"CompletionTime" => non_neg_integer(),
"CreationTime" => non_neg_integer(),
"FailureReason" => String.t() | atom(),
"LanguageCode" => list(any()),
"StartTime" => non_neg_integer()
}
"""
@type call_analytics_job_summary() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
transcription_job() :: %{
"CompletionTime" => non_neg_integer(),
"ContentRedaction" => content_redaction(),
"CreationTime" => non_neg_integer(),
"FailureReason" => String.t() | atom(),
"IdentifiedLanguageScore" => float(),
"IdentifyLanguage" => boolean(),
"IdentifyMultipleLanguages" => boolean(),
"JobExecutionSettings" => job_execution_settings(),
"LanguageCode" => list(any()),
"LanguageCodes" => list(language_code_item()),
"LanguageIdSettings" => map(),
"LanguageOptions" => list(list(any())()),
"Media" => media(),
"MediaFormat" => list(any()),
"MediaSampleRateHertz" => integer(),
"ModelSettings" => model_settings(),
"Settings" => settings(),
"StartTime" => non_neg_integer(),
"Subtitles" => subtitles_output(),
"Tags" => list(tag()),
"ToxicityDetection" => list(toxicity_detection_settings()),
"Transcript" => transcript(),
"TranscriptionJobName" => String.t() | atom(),
"TranscriptionJobStatus" => list(any())
}
"""
@type transcription_job() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
medical_transcription_job_summary() :: %{
"CompletionTime" => non_neg_integer(),
"ContentIdentificationType" => list(any()),
"CreationTime" => non_neg_integer(),
"FailureReason" => String.t() | atom(),
"LanguageCode" => list(any()),
"MedicalTranscriptionJobName" => String.t() | atom(),
"OutputLocationType" => list(any()),
"Specialty" => list(any()),
"StartTime" => non_neg_integer(),
"TranscriptionJobStatus" => list(any()),
"Type" => list(any())
}
"""
@type medical_transcription_job_summary() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
delete_call_analytics_job_response() :: %{}
"""
@type delete_call_analytics_job_response() :: %{}
@typedoc """
## Example:
delete_call_analytics_category_response() :: %{}
"""
@type delete_call_analytics_category_response() :: %{}
@typedoc """
## Example:
create_language_model_response() :: %{
"BaseModelName" => list(any()),
"InputDataConfig" => input_data_config(),
"LanguageCode" => list(any()),
"ModelName" => String.t() | atom(),
"ModelStatus" => list(any())
}
"""
@type create_language_model_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
create_vocabulary_filter_request() :: %{
optional("DataAccessRoleArn") => String.t() | atom(),
optional("Tags") => list(tag()),
optional("VocabularyFilterFileUri") => String.t() | atom(),
optional("Words") => list(String.t() | atom()),
required("LanguageCode") => list(any())
}
"""
@type create_vocabulary_filter_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
tag_resource_request() :: %{
required("Tags") => list(tag())
}
"""
@type tag_resource_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
internal_failure_exception() :: %{
"Message" => String.t() | atom()
}
"""
@type internal_failure_exception() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
delete_medical_transcription_job_request() :: %{}
"""
@type delete_medical_transcription_job_request() :: %{}
@typedoc """
## Example:
list_medical_transcription_jobs_response() :: %{
"MedicalTranscriptionJobSummaries" => list(medical_transcription_job_summary()),
"NextToken" => String.t() | atom(),
"Status" => list(any())
}
"""
@type list_medical_transcription_jobs_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
job_execution_settings() :: %{
"AllowDeferredExecution" => boolean(),
"DataAccessRoleArn" => String.t() | atom()
}
"""
@type job_execution_settings() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
absolute_time_range() :: %{
"EndTime" => float(),
"First" => float(),
"Last" => float(),
"StartTime" => float()
}
"""
@type absolute_time_range() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
list_language_models_request() :: %{
optional("MaxResults") => integer(),
optional("NameContains") => String.t() | atom(),
optional("NextToken") => String.t() | atom(),
optional("StatusEquals") => list(any())
}
"""
@type list_language_models_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
summarization() :: %{
"GenerateAbstractiveSummary" => boolean()
}
"""
@type summarization() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
input_data_config() :: %{
"DataAccessRoleArn" => String.t() | atom(),
"S3Uri" => String.t() | atom(),
"TuningDataS3Uri" => String.t() | atom()
}
"""
@type input_data_config() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
untag_resource_response() :: %{}
"""
@type untag_resource_response() :: %{}
@typedoc """
## Example:
non_talk_time_filter() :: %{
"AbsoluteTimeRange" => absolute_time_range(),
"Negate" => boolean(),
"RelativeTimeRange" => relative_time_range(),
"Threshold" => float()
}
"""
@type non_talk_time_filter() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
clinical_note_generation_settings() :: %{
"NoteTemplate" => list(any())
}
"""
@type clinical_note_generation_settings() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
start_medical_transcription_job_response() :: %{
"MedicalTranscriptionJob" => medical_transcription_job()
}
"""
@type start_medical_transcription_job_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
toxicity_detection_settings() :: %{
"ToxicityCategories" => list(list(any())())
}
"""
@type toxicity_detection_settings() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
delete_language_model_request() :: %{}
"""
@type delete_language_model_request() :: %{}
@typedoc """
## Example:
create_vocabulary_filter_response() :: %{
"LanguageCode" => list(any()),
"LastModifiedTime" => non_neg_integer(),
"VocabularyFilterName" => String.t() | atom()
}
"""
@type create_vocabulary_filter_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
list_transcription_jobs_request() :: %{
optional("JobNameContains") => String.t() | atom(),
optional("MaxResults") => integer(),
optional("NextToken") => String.t() | atom(),
optional("Status") => list(any())
}
"""
@type list_transcription_jobs_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
create_vocabulary_response() :: %{
"FailureReason" => String.t() | atom(),
"LanguageCode" => list(any()),
"LastModifiedTime" => non_neg_integer(),
"VocabularyName" => String.t() | atom(),
"VocabularyState" => list(any())
}
"""
@type create_vocabulary_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
update_vocabulary_filter_request() :: %{
optional("DataAccessRoleArn") => String.t() | atom(),
optional("VocabularyFilterFileUri") => String.t() | atom(),
optional("Words") => list(String.t() | atom())
}
"""
@type update_vocabulary_filter_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
medical_scribe_job_summary() :: %{
"CompletionTime" => non_neg_integer(),
"CreationTime" => non_neg_integer(),
"FailureReason" => String.t() | atom(),
"LanguageCode" => list(any()),
"MedicalScribeJobName" => String.t() | atom(),
"MedicalScribeJobStatus" => list(any()),
"StartTime" => non_neg_integer()
}
"""
@type medical_scribe_job_summary() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
transcription_job_summary() :: %{
"CompletionTime" => non_neg_integer(),
"ContentRedaction" => content_redaction(),
"CreationTime" => non_neg_integer(),
"FailureReason" => String.t() | atom(),
"IdentifiedLanguageScore" => float(),
"IdentifyLanguage" => boolean(),
"IdentifyMultipleLanguages" => boolean(),
"LanguageCode" => list(any()),
"LanguageCodes" => list(language_code_item()),
"ModelSettings" => model_settings(),
"OutputLocationType" => list(any()),
"StartTime" => non_neg_integer(),
"ToxicityDetection" => list(toxicity_detection_settings()),
"TranscriptionJobName" => String.t() | atom(),
"TranscriptionJobStatus" => list(any())
}
"""
@type transcription_job_summary() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
list_medical_vocabularies_request() :: %{
optional("MaxResults") => integer(),
optional("NameContains") => String.t() | atom(),
optional("NextToken") => String.t() | atom(),
optional("StateEquals") => list(any())
}
"""
@type list_medical_vocabularies_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
call_analytics_job() :: %{
"CallAnalyticsJobDetails" => call_analytics_job_details(),
"CallAnalyticsJobName" => String.t() | atom(),
"CallAnalyticsJobStatus" => list(any()),
"ChannelDefinitions" => list(channel_definition()),
"CompletionTime" => non_neg_integer(),
"CreationTime" => non_neg_integer(),
"DataAccessRoleArn" => String.t() | atom(),
"FailureReason" => String.t() | atom(),
"IdentifiedLanguageScore" => float(),
"LanguageCode" => list(any()),
"Media" => media(),
"MediaFormat" => list(any()),
"MediaSampleRateHertz" => integer(),
"Settings" => call_analytics_job_settings(),
"StartTime" => non_neg_integer(),
"Tags" => list(tag()),
"Transcript" => transcript()
}
"""
@type call_analytics_job() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
language_code_item() :: %{
"DurationInSeconds" => float(),
"LanguageCode" => list(any())
}
"""
@type language_code_item() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
list_vocabularies_request() :: %{
optional("MaxResults") => integer(),
optional("NameContains") => String.t() | atom(),
optional("NextToken") => String.t() | atom(),
optional("StateEquals") => list(any())
}
"""
@type list_vocabularies_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
transcript() :: %{
"RedactedTranscriptFileUri" => String.t() | atom(),
"TranscriptFileUri" => String.t() | atom()
}
"""
@type transcript() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
untag_resource_request() :: %{
required("TagKeys") => list(String.t() | atom())
}
"""
@type untag_resource_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
call_analytics_job_details() :: %{
"Skipped" => list(call_analytics_skipped_feature())
}
"""
@type call_analytics_job_details() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
list_medical_scribe_jobs_response() :: %{
"MedicalScribeJobSummaries" => list(medical_scribe_job_summary()),
"NextToken" => String.t() | atom(),
"Status" => list(any())
}
"""
@type list_medical_scribe_jobs_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
get_call_analytics_job_request() :: %{}
"""
@type get_call_analytics_job_request() :: %{}
@typedoc """
## Example:
update_vocabulary_request() :: %{
optional("DataAccessRoleArn") => String.t() | atom(),
optional("Phrases") => list(String.t() | atom()),
optional("VocabularyFileUri") => String.t() | atom(),
required("LanguageCode") => list(any())
}
"""
@type update_vocabulary_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
transcript_filter() :: %{
"AbsoluteTimeRange" => absolute_time_range(),
"Negate" => boolean(),
"ParticipantRole" => list(any()),
"RelativeTimeRange" => relative_time_range(),
"Targets" => list(String.t() | atom()),
"TranscriptFilterType" => list(any())
}
"""
@type transcript_filter() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
create_vocabulary_request() :: %{
optional("DataAccessRoleArn") => String.t() | atom(),
optional("Phrases") => list(String.t() | atom()),
optional("Tags") => list(tag()),
optional("VocabularyFileUri") => String.t() | atom(),
required("LanguageCode") => list(any())
}
"""
@type create_vocabulary_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
get_vocabulary_request() :: %{}
"""
@type get_vocabulary_request() :: %{}
@typedoc """
## Example:
create_language_model_request() :: %{
optional("Tags") => list(tag()),
required("BaseModelName") => list(any()),
required("InputDataConfig") => input_data_config(),
required("LanguageCode") => list(any())
}
"""
@type create_language_model_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
list_call_analytics_categories_response() :: %{
"Categories" => list(category_properties()),
"NextToken" => String.t() | atom()
}
"""
@type list_call_analytics_categories_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
start_call_analytics_job_response() :: %{
"CallAnalyticsJob" => call_analytics_job()
}
"""
@type start_call_analytics_job_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
update_medical_vocabulary_response() :: %{
"LanguageCode" => list(any()),
"LastModifiedTime" => non_neg_integer(),
"VocabularyName" => String.t() | atom(),
"VocabularyState" => list(any())
}
"""
@type update_medical_vocabulary_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
start_call_analytics_job_request() :: %{
optional("ChannelDefinitions") => list(channel_definition()),
optional("DataAccessRoleArn") => String.t() | atom(),
optional("OutputEncryptionKMSKeyId") => String.t() | atom(),
optional("OutputLocation") => String.t() | atom(),
optional("Settings") => call_analytics_job_settings(),
optional("Tags") => list(tag()),
required("Media") => media()
}
"""
@type start_call_analytics_job_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
content_redaction() :: %{
"PiiEntityTypes" => list(list(any())()),
"RedactionOutput" => list(any()),
"RedactionType" => list(any())
}
"""
@type content_redaction() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
medical_transcript() :: %{
"TranscriptFileUri" => String.t() | atom()
}
"""
@type medical_transcript() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
medical_transcription_job() :: %{
"CompletionTime" => non_neg_integer(),
"ContentIdentificationType" => list(any()),
"CreationTime" => non_neg_integer(),
"FailureReason" => String.t() | atom(),
"LanguageCode" => list(any()),
"Media" => media(),
"MediaFormat" => list(any()),
"MediaSampleRateHertz" => integer(),
"MedicalTranscriptionJobName" => String.t() | atom(),
"Settings" => medical_transcription_setting(),
"Specialty" => list(any()),
"StartTime" => non_neg_integer(),
"Tags" => list(tag()),
"Transcript" => medical_transcript(),
"TranscriptionJobStatus" => list(any()),
"Type" => list(any())
}
"""
@type medical_transcription_job() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
category_properties() :: %{
"CategoryName" => String.t() | atom(),
"CreateTime" => non_neg_integer(),
"InputType" => list(any()),
"LastUpdateTime" => non_neg_integer(),
"Rules" => list(list()),
"Tags" => list(tag())
}
"""
@type category_properties() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
get_transcription_job_request() :: %{}
"""
@type get_transcription_job_request() :: %{}
@typedoc """
## Example:
delete_medical_scribe_job_request() :: %{}
"""
@type delete_medical_scribe_job_request() :: %{}
@typedoc """
## Example:
vocabulary_filter_info() :: %{
"LanguageCode" => list(any()),
"LastModifiedTime" => non_neg_integer(),
"VocabularyFilterName" => String.t() | atom()
}
"""
@type vocabulary_filter_info() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
conflict_exception() :: %{
"Message" => String.t() | atom()
}
"""
@type conflict_exception() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
medical_scribe_settings() :: %{
"ChannelIdentification" => boolean(),
"ClinicalNoteGenerationSettings" => clinical_note_generation_settings(),
"MaxSpeakerLabels" => integer(),
"ShowSpeakerLabels" => boolean(),
"VocabularyFilterMethod" => list(any()),
"VocabularyFilterName" => String.t() | atom(),
"VocabularyName" => String.t() | atom()
}
"""
@type medical_scribe_settings() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
tag() :: %{
"Key" => String.t() | atom(),
"Value" => String.t() | atom()
}
"""
@type tag() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
delete_transcription_job_request() :: %{}
"""
@type delete_transcription_job_request() :: %{}
@typedoc """
## Example:
delete_call_analytics_job_request() :: %{}
"""
@type delete_call_analytics_job_request() :: %{}
@typedoc """
## Example:
sentiment_filter() :: %{
"AbsoluteTimeRange" => absolute_time_range(),
"Negate" => boolean(),
"ParticipantRole" => list(any()),
"RelativeTimeRange" => relative_time_range(),
"Sentiments" => list(list(any())())
}
"""
@type sentiment_filter() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
list_vocabulary_filters_request() :: %{
optional("MaxResults") => integer(),
optional("NameContains") => String.t() | atom(),
optional("NextToken") => String.t() | atom()
}
"""
@type list_vocabulary_filters_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
channel_definition() :: %{
"ChannelId" => integer(),
"ParticipantRole" => list(any())
}
"""
@type channel_definition() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
medical_transcription_setting() :: %{
"ChannelIdentification" => boolean(),
"MaxAlternatives" => integer(),
"MaxSpeakerLabels" => integer(),
"ShowAlternatives" => boolean(),
"ShowSpeakerLabels" => boolean(),
"VocabularyName" => String.t() | atom()
}
"""
@type medical_transcription_setting() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
not_found_exception() :: %{
"Message" => String.t() | atom()
}
"""
@type not_found_exception() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
call_analytics_skipped_feature() :: %{
"Feature" => list(any()),
"Message" => String.t() | atom(),
"ReasonCode" => list(any())
}
"""
@type call_analytics_skipped_feature() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
list_medical_vocabularies_response() :: %{
"NextToken" => String.t() | atom(),
"Status" => list(any()),
"Vocabularies" => list(vocabulary_info())
}
"""
@type list_medical_vocabularies_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
settings() :: %{
"ChannelIdentification" => boolean(),
"MaxAlternatives" => integer(),
"MaxSpeakerLabels" => integer(),
"ShowAlternatives" => boolean(),
"ShowSpeakerLabels" => boolean(),
"VocabularyFilterMethod" => list(any()),
"VocabularyFilterName" => String.t() | atom(),
"VocabularyName" => String.t() | atom()
}
"""
@type settings() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
model_settings() :: %{
"LanguageModelName" => String.t() | atom()
}
"""
@type model_settings() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
list_transcription_jobs_response() :: %{
"NextToken" => String.t() | atom(),
"Status" => list(any()),
"TranscriptionJobSummaries" => list(transcription_job_summary())
}
"""
@type list_transcription_jobs_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
list_tags_for_resource_response() :: %{
"ResourceArn" => String.t() | atom(),
"Tags" => list(tag())
}
"""
@type list_tags_for_resource_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
medical_scribe_job() :: %{
"ChannelDefinitions" => list(medical_scribe_channel_definition()),
"CompletionTime" => non_neg_integer(),
"CreationTime" => non_neg_integer(),
"DataAccessRoleArn" => String.t() | atom(),
"FailureReason" => String.t() | atom(),
"LanguageCode" => list(any()),
"Media" => media(),
"MedicalScribeContextProvided" => boolean(),
"MedicalScribeJobName" => String.t() | atom(),
"MedicalScribeJobStatus" => list(any()),
"MedicalScribeOutput" => medical_scribe_output(),
"Settings" => medical_scribe_settings(),
"StartTime" => non_neg_integer(),
"Tags" => list(tag())
}
"""
@type medical_scribe_job() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
medical_scribe_patient_context() :: %{
"Pronouns" => list(any())
}
"""
@type medical_scribe_patient_context() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
language_id_settings() :: %{
"LanguageModelName" => String.t() | atom(),
"VocabularyFilterName" => String.t() | atom(),
"VocabularyName" => String.t() | atom()
}
"""
@type language_id_settings() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
get_call_analytics_job_response() :: %{
"CallAnalyticsJob" => call_analytics_job()
}
"""
@type get_call_analytics_job_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
media() :: %{
"MediaFileUri" => String.t() | atom(),
"RedactedMediaFileUri" => String.t() | atom()
}
"""
@type media() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
update_vocabulary_filter_response() :: %{
"LanguageCode" => list(any()),
"LastModifiedTime" => non_neg_integer(),
"VocabularyFilterName" => String.t() | atom()
}
"""
@type update_vocabulary_filter_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
language_model() :: %{
"BaseModelName" => list(any()),
"CreateTime" => non_neg_integer(),
"FailureReason" => String.t() | atom(),
"InputDataConfig" => input_data_config(),
"LanguageCode" => list(any()),
"LastModifiedTime" => non_neg_integer(),
"ModelName" => String.t() | atom(),
"ModelStatus" => list(any()),
"UpgradeAvailability" => boolean()
}
"""
@type language_model() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
update_medical_vocabulary_request() :: %{
required("LanguageCode") => list(any()),
required("VocabularyFileUri") => String.t() | atom()
}
"""
@type update_medical_vocabulary_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
update_call_analytics_category_request() :: %{
optional("InputType") => list(any()),
required("Rules") => list(list())
}
"""
@type update_call_analytics_category_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
start_medical_transcription_job_request() :: %{
optional("ContentIdentificationType") => list(any()),
optional("KMSEncryptionContext") => map(),
optional("MediaFormat") => list(any()),
optional("MediaSampleRateHertz") => integer(),
optional("OutputEncryptionKMSKeyId") => String.t() | atom(),
optional("OutputKey") => String.t() | atom(),
optional("Settings") => medical_transcription_setting(),
optional("Tags") => list(tag()),
required("LanguageCode") => list(any()),
required("Media") => media(),
required("OutputBucketName") => String.t() | atom(),
required("Specialty") => list(any()),
required("Type") => list(any())
}
"""
@type start_medical_transcription_job_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
get_medical_scribe_job_request() :: %{}
"""
@type get_medical_scribe_job_request() :: %{}
@typedoc """
## Example:
list_call_analytics_jobs_response() :: %{
"CallAnalyticsJobSummaries" => list(call_analytics_job_summary()),
"NextToken" => String.t() | atom(),
"Status" => list(any())
}
"""
@type list_call_analytics_jobs_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
start_transcription_job_response() :: %{
"TranscriptionJob" => transcription_job()
}
"""
@type start_transcription_job_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
subtitles() :: %{
"Formats" => list(list(any())()),
"OutputStartIndex" => integer()
}
"""
@type subtitles() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
list_language_models_response() :: %{
"Models" => list(language_model()),
"NextToken" => String.t() | atom()
}
"""
@type list_language_models_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
update_call_analytics_category_response() :: %{
"CategoryProperties" => category_properties()
}
"""
@type update_call_analytics_category_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
describe_language_model_response() :: %{
"LanguageModel" => language_model()
}
"""
@type describe_language_model_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
medical_scribe_output() :: %{
"ClinicalDocumentUri" => String.t() | atom(),
"TranscriptFileUri" => String.t() | atom()
}
"""
@type medical_scribe_output() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
get_medical_transcription_job_request() :: %{}
"""
@type get_medical_transcription_job_request() :: %{}
@typedoc """
## Example:
delete_vocabulary_filter_request() :: %{}
"""
@type delete_vocabulary_filter_request() :: %{}
@typedoc """
## Example:
tag_resource_response() :: %{}
"""
@type tag_resource_response() :: %{}
@typedoc """
## Example:
describe_language_model_request() :: %{}
"""
@type describe_language_model_request() :: %{}
@typedoc """
## Example:
list_call_analytics_jobs_request() :: %{
optional("JobNameContains") => String.t() | atom(),
optional("MaxResults") => integer(),
optional("NextToken") => String.t() | atom(),
optional("Status") => list(any())
}
"""
@type list_call_analytics_jobs_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
delete_medical_vocabulary_request() :: %{}
"""
@type delete_medical_vocabulary_request() :: %{}
@typedoc """
## Example:
list_tags_for_resource_request() :: %{}
"""
@type list_tags_for_resource_request() :: %{}
@typedoc """
## Example:
vocabulary_info() :: %{
"LanguageCode" => list(any()),
"LastModifiedTime" => non_neg_integer(),
"VocabularyName" => String.t() | atom(),
"VocabularyState" => list(any())
}
"""
@type vocabulary_info() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
call_analytics_job_settings() :: %{
"ContentRedaction" => content_redaction(),
"LanguageIdSettings" => map(),
"LanguageModelName" => String.t() | atom(),
"LanguageOptions" => list(list(any())()),
"Summarization" => summarization(),
"VocabularyFilterMethod" => list(any()),
"VocabularyFilterName" => String.t() | atom(),
"VocabularyName" => String.t() | atom()
}
"""
@type call_analytics_job_settings() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
delete_vocabulary_request() :: %{}
"""
@type delete_vocabulary_request() :: %{}
@typedoc """
## Example:
create_medical_vocabulary_response() :: %{
"FailureReason" => String.t() | atom(),
"LanguageCode" => list(any()),
"LastModifiedTime" => non_neg_integer(),
"VocabularyName" => String.t() | atom(),
"VocabularyState" => list(any())
}
"""
@type create_medical_vocabulary_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
start_medical_scribe_job_request() :: %{
optional("ChannelDefinitions") => list(medical_scribe_channel_definition()),
optional("KMSEncryptionContext") => map(),
optional("MedicalScribeContext") => medical_scribe_context(),
optional("OutputEncryptionKMSKeyId") => String.t() | atom(),
optional("Tags") => list(tag()),
required("DataAccessRoleArn") => String.t() | atom(),
required("Media") => media(),
required("OutputBucketName") => String.t() | atom(),
required("Settings") => medical_scribe_settings()
}
"""
@type start_medical_scribe_job_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
update_vocabulary_response() :: %{
"LanguageCode" => list(any()),
"LastModifiedTime" => non_neg_integer(),
"VocabularyName" => String.t() | atom(),
"VocabularyState" => list(any())
}
"""
@type update_vocabulary_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
limit_exceeded_exception() :: %{
"Message" => String.t() | atom()
}
"""
@type limit_exceeded_exception() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
get_medical_vocabulary_response() :: %{
"DownloadUri" => String.t() | atom(),
"FailureReason" => String.t() | atom(),
"LanguageCode" => list(any()),
"LastModifiedTime" => non_neg_integer(),
"VocabularyName" => String.t() | atom(),
"VocabularyState" => list(any())
}
"""
@type get_medical_vocabulary_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
get_call_analytics_category_request() :: %{}
"""
@type get_call_analytics_category_request() :: %{}
@typedoc """
## Example:
bad_request_exception() :: %{
"Message" => String.t() | atom()
}
"""
@type bad_request_exception() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
list_medical_transcription_jobs_request() :: %{
optional("JobNameContains") => String.t() | atom(),
optional("MaxResults") => integer(),
optional("NextToken") => String.t() | atom(),
optional("Status") => list(any())
}
"""
@type list_medical_transcription_jobs_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
get_medical_vocabulary_request() :: %{}
"""
@type get_medical_vocabulary_request() :: %{}
@typedoc """
## Example:
list_vocabulary_filters_response() :: %{
"NextToken" => String.t() | atom(),
"VocabularyFilters" => list(vocabulary_filter_info())
}
"""
@type list_vocabulary_filters_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
get_vocabulary_filter_request() :: %{}
"""
@type get_vocabulary_filter_request() :: %{}
@typedoc """
## Example:
medical_scribe_context() :: %{
"PatientContext" => medical_scribe_patient_context()
}
"""
@type medical_scribe_context() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
interruption_filter() :: %{
"AbsoluteTimeRange" => absolute_time_range(),
"Negate" => boolean(),
"ParticipantRole" => list(any()),
"RelativeTimeRange" => relative_time_range(),
"Threshold" => float()
}
"""
@type interruption_filter() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
get_medical_transcription_job_response() :: %{
"MedicalTranscriptionJob" => medical_transcription_job()
}
"""
@type get_medical_transcription_job_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
get_vocabulary_response() :: %{
"DownloadUri" => String.t() | atom(),
"FailureReason" => String.t() | atom(),
"LanguageCode" => list(any()),
"LastModifiedTime" => non_neg_integer(),
"VocabularyName" => String.t() | atom(),
"VocabularyState" => list(any())
}
"""
@type get_vocabulary_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
delete_call_analytics_category_request() :: %{}
"""
@type delete_call_analytics_category_request() :: %{}
@typedoc """
## Example:
get_vocabulary_filter_response() :: %{
"DownloadUri" => String.t() | atom(),
"LanguageCode" => list(any()),
"LastModifiedTime" => non_neg_integer(),
"VocabularyFilterName" => String.t() | atom()
}
"""
@type get_vocabulary_filter_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
create_medical_vocabulary_request() :: %{
optional("Tags") => list(tag()),
required("LanguageCode") => list(any()),
required("VocabularyFileUri") => String.t() | atom()
}
"""
@type create_medical_vocabulary_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
list_medical_scribe_jobs_request() :: %{
optional("JobNameContains") => String.t() | atom(),
optional("MaxResults") => integer(),
optional("NextToken") => String.t() | atom(),
optional("Status") => list(any())
}
"""
@type list_medical_scribe_jobs_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
relative_time_range() :: %{
"EndPercentage" => integer(),
"First" => integer(),
"Last" => integer(),
"StartPercentage" => integer()
}
"""
@type relative_time_range() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
medical_scribe_channel_definition() :: %{
"ChannelId" => integer(),
"ParticipantRole" => list(any())
}
"""
@type medical_scribe_channel_definition() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
start_transcription_job_request() :: %{
optional("ContentRedaction") => content_redaction(),
optional("IdentifyLanguage") => boolean(),
optional("IdentifyMultipleLanguages") => boolean(),
optional("JobExecutionSettings") => job_execution_settings(),
optional("KMSEncryptionContext") => map(),
optional("LanguageCode") => list(any()),
optional("LanguageIdSettings") => map(),
optional("LanguageOptions") => list(list(any())()),
optional("MediaFormat") => list(any()),
optional("MediaSampleRateHertz") => integer(),
optional("ModelSettings") => model_settings(),
optional("OutputBucketName") => String.t() | atom(),
optional("OutputEncryptionKMSKeyId") => String.t() | atom(),
optional("OutputKey") => String.t() | atom(),
optional("Settings") => settings(),
optional("Subtitles") => subtitles(),
optional("Tags") => list(tag()),
optional("ToxicityDetection") => list(toxicity_detection_settings()),
required("Media") => media()
}
"""
@type start_transcription_job_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
get_call_analytics_category_response() :: %{
"CategoryProperties" => category_properties()
}
"""
@type get_call_analytics_category_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
create_call_analytics_category_request() :: %{
optional("InputType") => list(any()),
optional("Tags") => list(tag()),
required("Rules") => list(list())
}
"""
@type create_call_analytics_category_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
start_medical_scribe_job_response() :: %{
"MedicalScribeJob" => medical_scribe_job()
}
"""
@type start_medical_scribe_job_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
list_call_analytics_categories_request() :: %{
optional("MaxResults") => integer(),
optional("NextToken") => String.t() | atom()
}
"""
@type list_call_analytics_categories_request() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
create_call_analytics_category_response() :: %{
"CategoryProperties" => category_properties()
}
"""
@type create_call_analytics_category_response() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
subtitles_output() :: %{
"Formats" => list(list(any())()),
"OutputStartIndex" => integer(),
"SubtitleFileUris" => list(String.t() | atom())
}
"""
@type subtitles_output() :: %{(String.t() | atom()) => any()}
@typedoc """
## Example:
get_medical_scribe_job_response() :: %{
"MedicalScribeJob" => medical_scribe_job()
}
"""
@type get_medical_scribe_job_response() :: %{(String.t() | atom()) => any()}
@type create_call_analytics_category_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| conflict_exception()
| internal_failure_exception()
@type create_language_model_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| conflict_exception()
| internal_failure_exception()
@type create_medical_vocabulary_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| conflict_exception()
| internal_failure_exception()
@type create_vocabulary_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| conflict_exception()
| internal_failure_exception()
@type create_vocabulary_filter_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| conflict_exception()
| internal_failure_exception()
@type delete_call_analytics_category_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| internal_failure_exception()
@type delete_call_analytics_job_errors() ::
bad_request_exception() | limit_exceeded_exception() | internal_failure_exception()
@type delete_language_model_errors() ::
bad_request_exception() | limit_exceeded_exception() | internal_failure_exception()
@type delete_medical_scribe_job_errors() ::
bad_request_exception() | limit_exceeded_exception() | internal_failure_exception()
@type delete_medical_transcription_job_errors() ::
bad_request_exception() | limit_exceeded_exception() | internal_failure_exception()
@type delete_medical_vocabulary_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| internal_failure_exception()
@type delete_transcription_job_errors() ::
bad_request_exception() | limit_exceeded_exception() | internal_failure_exception()
@type delete_vocabulary_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| internal_failure_exception()
@type delete_vocabulary_filter_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| internal_failure_exception()
@type describe_language_model_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| internal_failure_exception()
@type get_call_analytics_category_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| internal_failure_exception()
@type get_call_analytics_job_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| internal_failure_exception()
@type get_medical_scribe_job_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| internal_failure_exception()
@type get_medical_transcription_job_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| internal_failure_exception()
@type get_medical_vocabulary_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| internal_failure_exception()
@type get_transcription_job_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| internal_failure_exception()
@type get_vocabulary_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| internal_failure_exception()
@type get_vocabulary_filter_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| internal_failure_exception()
@type list_call_analytics_categories_errors() ::
bad_request_exception() | limit_exceeded_exception() | internal_failure_exception()
@type list_call_analytics_jobs_errors() ::
bad_request_exception() | limit_exceeded_exception() | internal_failure_exception()
@type list_language_models_errors() ::
bad_request_exception() | limit_exceeded_exception() | internal_failure_exception()
@type list_medical_scribe_jobs_errors() ::
bad_request_exception() | limit_exceeded_exception() | internal_failure_exception()
@type list_medical_transcription_jobs_errors() ::
bad_request_exception() | limit_exceeded_exception() | internal_failure_exception()
@type list_medical_vocabularies_errors() ::
bad_request_exception() | limit_exceeded_exception() | internal_failure_exception()
@type list_tags_for_resource_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| internal_failure_exception()
@type list_transcription_jobs_errors() ::
bad_request_exception() | limit_exceeded_exception() | internal_failure_exception()
@type list_vocabularies_errors() ::
bad_request_exception() | limit_exceeded_exception() | internal_failure_exception()
@type list_vocabulary_filters_errors() ::
bad_request_exception() | limit_exceeded_exception() | internal_failure_exception()
@type start_call_analytics_job_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| conflict_exception()
| internal_failure_exception()
@type start_medical_scribe_job_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| conflict_exception()
| internal_failure_exception()
@type start_medical_transcription_job_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| conflict_exception()
| internal_failure_exception()
@type start_transcription_job_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| conflict_exception()
| internal_failure_exception()
@type tag_resource_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| conflict_exception()
| internal_failure_exception()
@type untag_resource_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| conflict_exception()
| internal_failure_exception()
@type update_call_analytics_category_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| conflict_exception()
| internal_failure_exception()
@type update_medical_vocabulary_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| conflict_exception()
| internal_failure_exception()
@type update_vocabulary_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| conflict_exception()
| internal_failure_exception()
@type update_vocabulary_filter_errors() ::
bad_request_exception()
| limit_exceeded_exception()
| not_found_exception()
| internal_failure_exception()
def metadata do
%{
api_version: "2017-10-26",
content_type: "application/x-amz-json-1.1",
credential_scope: nil,
endpoint_prefix: "transcribe",
global?: false,
hostname: nil,
protocol: "json",
service_id: "Transcribe",
signature_version: "v4",
signing_name: "transcribe",
target_prefix: "Transcribe"
}
end
@doc """
Creates a new Call Analytics category.
All categories are automatically applied to your Call Analytics transcriptions.
Note that in
order to apply categories to your transcriptions, you must create them before
submitting your
transcription request, as categories cannot be applied retroactively.
When creating a new category, you can use the `InputType` parameter to
label the category as a `POST_CALL` or a `REAL_TIME` category.
`POST_CALL` categories can only be applied to post-call transcriptions and
`REAL_TIME` categories can only be applied to real-time transcriptions. If you
do not include `InputType`, your category is created as a
`POST_CALL` category by default.
Call Analytics categories are composed of rules. For each category, you must
create
between 1 and 20 rules. Rules can include these parameters: , , , and .
To update an existing category, see .
To learn more about Call Analytics categories, see [Creating categories for post-call
transcriptions](https://docs.aws.amazon.com/transcribe/latest/dg/tca-categories-batch.html)
and [Creating categories for real-time
transcriptions](https://docs.aws.amazon.com/transcribe/latest/dg/tca-categories-stream.html).
"""
@spec create_call_analytics_category(map(), create_call_analytics_category_request(), list()) ::
{:ok, create_call_analytics_category_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, create_call_analytics_category_errors()}
def create_call_analytics_category(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "CreateCallAnalyticsCategory", input, options)
end
@doc """
Creates a new custom language model.
When creating a new custom language model, you must specify:
*
If you want a Wideband (audio sample rates over 16,000 Hz) or Narrowband
(audio sample rates under 16,000 Hz) base model
*
The location of your training and tuning files (this must be an Amazon S3 URI)
*
The language of your model
*
A unique name for your model
"""
@spec create_language_model(map(), create_language_model_request(), list()) ::
{:ok, create_language_model_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, create_language_model_errors()}
def create_language_model(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "CreateLanguageModel", input, options)
end
@doc """
Creates a new custom medical vocabulary.
Before creating a new custom medical vocabulary, you must first upload a text
file
that contains your vocabulary table into an Amazon S3 bucket.
Note that this differs from , where you can
include a list of terms within your request using the `Phrases` flag;
`CreateMedicalVocabulary` does not support the `Phrases`
flag and only accepts vocabularies in table format.
Each language has a character set that contains all allowed characters for that
specific language. If you use unsupported characters, your custom vocabulary
request
fails. Refer to [Character Sets for Custom Vocabularies](https://docs.aws.amazon.com/transcribe/latest/dg/charsets.html) to
get the character set for your
language.
For more information, see [Custom vocabularies](https://docs.aws.amazon.com/transcribe/latest/dg/custom-vocabulary.html).
"""
@spec create_medical_vocabulary(map(), create_medical_vocabulary_request(), list()) ::
{:ok, create_medical_vocabulary_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, create_medical_vocabulary_errors()}
def create_medical_vocabulary(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "CreateMedicalVocabulary", input, options)
end
@doc """
Creates a new custom vocabulary.
When creating a new custom vocabulary, you can either upload a text file that
contains
your new entries, phrases, and terms into an Amazon S3 bucket and include the
URI in your request. Or you can include a list of terms directly in your request
using
the `Phrases` flag.
Each language has a character set that contains all allowed characters for that
specific language. If you use unsupported characters, your custom vocabulary
request
fails. Refer to [Character Sets for Custom Vocabularies](https://docs.aws.amazon.com/transcribe/latest/dg/charsets.html) to
get the character set for your
language.
For more information, see [Custom vocabularies](https://docs.aws.amazon.com/transcribe/latest/dg/custom-vocabulary.html).
"""
@spec create_vocabulary(map(), create_vocabulary_request(), list()) ::
{:ok, create_vocabulary_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, create_vocabulary_errors()}
def create_vocabulary(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "CreateVocabulary", input, options)
end
@doc """
Creates a new custom vocabulary filter.
You can use custom vocabulary filters to mask, delete, or flag specific words
from
your transcript. Custom vocabulary filters are commonly used to mask profanity
in
transcripts.
Each language has a character set that contains all allowed characters for that
specific language. If you use unsupported characters, your custom vocabulary
filter
request fails. Refer to [Character Sets for Custom Vocabularies](https://docs.aws.amazon.com/transcribe/latest/dg/charsets.html) to
get the character set for your language.
For more information, see [Vocabulary filtering](https://docs.aws.amazon.com/transcribe/latest/dg/vocabulary-filtering.html).
"""
@spec create_vocabulary_filter(map(), create_vocabulary_filter_request(), list()) ::
{:ok, create_vocabulary_filter_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, create_vocabulary_filter_errors()}
def create_vocabulary_filter(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "CreateVocabularyFilter", input, options)
end
@doc """
Deletes a Call Analytics category.
To use this operation, specify the name of the
category you want to delete using `CategoryName`. Category names are case
sensitive.
"""
@spec delete_call_analytics_category(map(), delete_call_analytics_category_request(), list()) ::
{:ok, delete_call_analytics_category_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, delete_call_analytics_category_errors()}
def delete_call_analytics_category(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "DeleteCallAnalyticsCategory", input, options)
end
@doc """
Deletes a Call Analytics job.
To use this operation, specify the name of the job you
want to delete using `CallAnalyticsJobName`. Job names are case
sensitive.
"""
@spec delete_call_analytics_job(map(), delete_call_analytics_job_request(), list()) ::
{:ok, delete_call_analytics_job_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, delete_call_analytics_job_errors()}
def delete_call_analytics_job(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "DeleteCallAnalyticsJob", input, options)
end
@doc """
Deletes a custom language model.
To use this operation, specify the name of the
language model you want to delete using `ModelName`. custom language model
names are case sensitive.
"""
@spec delete_language_model(map(), delete_language_model_request(), list()) ::
{:ok, nil, any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, delete_language_model_errors()}
def delete_language_model(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "DeleteLanguageModel", input, options)
end
@doc """
Deletes a Medical Scribe job.
To use this operation, specify the name of the
job you want to delete using `MedicalScribeJobName`. Job names are
case sensitive.
"""
@spec delete_medical_scribe_job(map(), delete_medical_scribe_job_request(), list()) ::
{:ok, nil, any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, delete_medical_scribe_job_errors()}
def delete_medical_scribe_job(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "DeleteMedicalScribeJob", input, options)
end
@doc """
Deletes a medical transcription job.
To use this operation, specify the name of the
job you want to delete using `MedicalTranscriptionJobName`. Job names are
case sensitive.
"""
@spec delete_medical_transcription_job(
map(),
delete_medical_transcription_job_request(),
list()
) ::
{:ok, nil, any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, delete_medical_transcription_job_errors()}
def delete_medical_transcription_job(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "DeleteMedicalTranscriptionJob", input, options)
end
@doc """
Deletes a custom medical vocabulary.
To use this operation, specify the name of the
custom vocabulary you want to delete using `VocabularyName`. Custom
vocabulary names are case sensitive.
"""
@spec delete_medical_vocabulary(map(), delete_medical_vocabulary_request(), list()) ::
{:ok, nil, any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, delete_medical_vocabulary_errors()}
def delete_medical_vocabulary(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "DeleteMedicalVocabulary", input, options)
end
@doc """
Deletes a transcription job.
To use this operation, specify the name of the job you
want to delete using `TranscriptionJobName`. Job names are case
sensitive.
"""
@spec delete_transcription_job(map(), delete_transcription_job_request(), list()) ::
{:ok, nil, any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, delete_transcription_job_errors()}
def delete_transcription_job(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "DeleteTranscriptionJob", input, options)
end
@doc """
Deletes a custom vocabulary.
To use this operation, specify the name of the custom
vocabulary you want to delete using `VocabularyName`. Custom vocabulary names
are case sensitive.
"""
@spec delete_vocabulary(map(), delete_vocabulary_request(), list()) ::
{:ok, nil, any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, delete_vocabulary_errors()}
def delete_vocabulary(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "DeleteVocabulary", input, options)
end
@doc """
Deletes a custom vocabulary filter.
To use this operation, specify the name of the
custom vocabulary filter you want to delete using `VocabularyFilterName`.
Custom vocabulary filter names are case sensitive.
"""
@spec delete_vocabulary_filter(map(), delete_vocabulary_filter_request(), list()) ::
{:ok, nil, any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, delete_vocabulary_filter_errors()}
def delete_vocabulary_filter(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "DeleteVocabularyFilter", input, options)
end
@doc """
Provides information about the specified custom language model.
This operation also shows if the base language model that you 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 you tried to create a new custom language model and the request wasn't
successful,
you can use `DescribeLanguageModel` to help identify the reason for this
failure.
"""
@spec describe_language_model(map(), describe_language_model_request(), list()) ::
{:ok, describe_language_model_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, describe_language_model_errors()}
def describe_language_model(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "DescribeLanguageModel", input, options)
end
@doc """
Provides information about the specified Call Analytics category.
To get a list of your Call Analytics categories, use the operation.
"""
@spec get_call_analytics_category(map(), get_call_analytics_category_request(), list()) ::
{:ok, get_call_analytics_category_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, get_call_analytics_category_errors()}
def get_call_analytics_category(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "GetCallAnalyticsCategory", input, options)
end
@doc """
Provides information about the specified Call Analytics job.
To view the job's status, refer to `CallAnalyticsJobStatus`. If the status
is `COMPLETED`, the job is finished. You can find your completed transcript
at the URI specified in `TranscriptFileUri`. If the status is
`FAILED`, `FailureReason` provides details on why your
transcription job failed.
If you enabled personally identifiable information (PII) redaction, the redacted
transcript appears at the location specified in
`RedactedTranscriptFileUri`.
If you chose to redact the audio in your media file, you can find your redacted
media
file at the location specified in `RedactedMediaFileUri`.
To get a list of your Call Analytics jobs, use the operation.
"""
@spec get_call_analytics_job(map(), get_call_analytics_job_request(), list()) ::
{:ok, get_call_analytics_job_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, get_call_analytics_job_errors()}
def get_call_analytics_job(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "GetCallAnalyticsJob", input, options)
end
@doc """
Provides information about the specified Medical Scribe job.
To view the status of the specified medical transcription job, check the
`MedicalScribeJobStatus` field. If the status is `COMPLETED`,
the job is finished. You can find the results at the location specified in
`MedicalScribeOutput`.
If the status is `FAILED`, `FailureReason` provides details on why your Medical
Scribe job
failed.
To get a list of your Medical Scribe jobs, use the operation.
"""
@spec get_medical_scribe_job(map(), get_medical_scribe_job_request(), list()) ::
{:ok, get_medical_scribe_job_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, get_medical_scribe_job_errors()}
def get_medical_scribe_job(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "GetMedicalScribeJob", input, options)
end
@doc """
Provides information about the specified medical transcription job.
To view the status of the specified medical transcription job, check the
`TranscriptionJobStatus` field. If the status is `COMPLETED`,
the job is finished. You can find the results at the location specified in
`TranscriptFileUri`. If the status is `FAILED`,
`FailureReason` provides details on why your transcription job
failed.
To get a list of your medical transcription jobs, use the operation.
"""
@spec get_medical_transcription_job(map(), get_medical_transcription_job_request(), list()) ::
{:ok, get_medical_transcription_job_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, get_medical_transcription_job_errors()}
def get_medical_transcription_job(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "GetMedicalTranscriptionJob", input, options)
end
@doc """
Provides information about the specified custom medical vocabulary.
To view the status of the specified custom medical vocabulary, check the
`VocabularyState` field. If the status is `READY`, your custom
vocabulary is available to use. If the status is `FAILED`,
`FailureReason` provides details on why your vocabulary failed.
To get a list of your custom medical vocabularies, use the operation.
"""
@spec get_medical_vocabulary(map(), get_medical_vocabulary_request(), list()) ::
{:ok, get_medical_vocabulary_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, get_medical_vocabulary_errors()}
def get_medical_vocabulary(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "GetMedicalVocabulary", input, options)
end
@doc """
Provides information about the specified transcription job.
To view the status of the specified transcription job, check the
`TranscriptionJobStatus` field. If the status is `COMPLETED`,
the job is finished. You can find the results at the location specified in
`TranscriptFileUri`. If the status is `FAILED`,
`FailureReason` provides details on why your transcription job
failed.
If you enabled content redaction, the redacted transcript can be found at the
location
specified in `RedactedTranscriptFileUri`.
To get a list of your transcription jobs, use the operation.
"""
@spec get_transcription_job(map(), get_transcription_job_request(), list()) ::
{:ok, get_transcription_job_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, get_transcription_job_errors()}
def get_transcription_job(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "GetTranscriptionJob", input, options)
end
@doc """
Provides information about the specified custom vocabulary.
To view the status of the specified custom vocabulary, check the
`VocabularyState` field. If the status is `READY`, your custom
vocabulary is available to use. If the status is `FAILED`,
`FailureReason` provides details on why your custom vocabulary
failed.
To get a list of your custom vocabularies, use the operation.
"""
@spec get_vocabulary(map(), get_vocabulary_request(), list()) ::
{:ok, get_vocabulary_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, get_vocabulary_errors()}
def get_vocabulary(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "GetVocabulary", input, options)
end
@doc """
Provides information about the specified custom vocabulary filter.
To get a list of your custom vocabulary filters, use the operation.
"""
@spec get_vocabulary_filter(map(), get_vocabulary_filter_request(), list()) ::
{:ok, get_vocabulary_filter_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, get_vocabulary_filter_errors()}
def get_vocabulary_filter(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "GetVocabularyFilter", input, options)
end
@doc """
Provides a list of Call Analytics categories, including all rules that make up
each
category.
To get detailed information about a specific Call Analytics category, use the
operation.
"""
@spec list_call_analytics_categories(map(), list_call_analytics_categories_request(), list()) ::
{:ok, list_call_analytics_categories_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, list_call_analytics_categories_errors()}
def list_call_analytics_categories(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "ListCallAnalyticsCategories", input, options)
end
@doc """
Provides a list of Call Analytics jobs that match the specified criteria.
If no
criteria are specified, all Call Analytics jobs are returned.
To get detailed information about a specific Call Analytics job, use the
operation.
"""
@spec list_call_analytics_jobs(map(), list_call_analytics_jobs_request(), list()) ::
{:ok, list_call_analytics_jobs_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, list_call_analytics_jobs_errors()}
def list_call_analytics_jobs(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "ListCallAnalyticsJobs", input, options)
end
@doc """
Provides a list of custom language models that match the specified criteria.
If no
criteria are specified, all custom language models are returned.
To get detailed information about a specific custom language model, use the
operation.
"""
@spec list_language_models(map(), list_language_models_request(), list()) ::
{:ok, list_language_models_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, list_language_models_errors()}
def list_language_models(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "ListLanguageModels", input, options)
end
@doc """
Provides a list of Medical Scribe jobs that match the specified criteria.
If no
criteria are specified, all Medical Scribe jobs are returned.
To get detailed information about a specific Medical Scribe job, use the
operation.
"""
@spec list_medical_scribe_jobs(map(), list_medical_scribe_jobs_request(), list()) ::
{:ok, list_medical_scribe_jobs_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, list_medical_scribe_jobs_errors()}
def list_medical_scribe_jobs(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "ListMedicalScribeJobs", input, options)
end
@doc """
Provides a list of medical transcription jobs that match the specified criteria.
If no
criteria are specified, all medical transcription jobs are returned.
To get detailed information about a specific medical transcription job, use the
operation.
"""
@spec list_medical_transcription_jobs(map(), list_medical_transcription_jobs_request(), list()) ::
{:ok, list_medical_transcription_jobs_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, list_medical_transcription_jobs_errors()}
def list_medical_transcription_jobs(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "ListMedicalTranscriptionJobs", input, options)
end
@doc """
Provides a list of custom medical vocabularies that match the specified
criteria.
If
no criteria are specified, all custom medical vocabularies are returned.
To get detailed information about a specific custom medical vocabulary, use the
operation.
"""
@spec list_medical_vocabularies(map(), list_medical_vocabularies_request(), list()) ::
{:ok, list_medical_vocabularies_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, list_medical_vocabularies_errors()}
def list_medical_vocabularies(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "ListMedicalVocabularies", input, options)
end
@doc """
Lists all tags associated with the specified transcription job, vocabulary,
model, or
resource.
To learn more about using tags with Amazon Transcribe, refer to [Tagging resources](https://docs.aws.amazon.com/transcribe/latest/dg/tagging.html).
"""
@spec list_tags_for_resource(map(), list_tags_for_resource_request(), list()) ::
{:ok, list_tags_for_resource_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, list_tags_for_resource_errors()}
def list_tags_for_resource(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "ListTagsForResource", input, options)
end
@doc """
Provides a list of transcription jobs that match the specified criteria.
If no
criteria are specified, all transcription jobs are returned.
To get detailed information about a specific transcription job, use the
operation.
"""
@spec list_transcription_jobs(map(), list_transcription_jobs_request(), list()) ::
{:ok, list_transcription_jobs_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, list_transcription_jobs_errors()}
def list_transcription_jobs(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "ListTranscriptionJobs", input, options)
end
@doc """
Provides a list of custom vocabularies that match the specified criteria.
If no
criteria are specified, all custom vocabularies are returned.
To get detailed information about a specific custom vocabulary, use the
operation.
"""
@spec list_vocabularies(map(), list_vocabularies_request(), list()) ::
{:ok, list_vocabularies_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, list_vocabularies_errors()}
def list_vocabularies(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "ListVocabularies", input, options)
end
@doc """
Provides a list of custom vocabulary filters that match the specified criteria.
If no
criteria are specified, all custom vocabularies are returned.
To get detailed information about a specific custom vocabulary filter, use the
operation.
"""
@spec list_vocabulary_filters(map(), list_vocabulary_filters_request(), list()) ::
{:ok, list_vocabulary_filters_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, list_vocabulary_filters_errors()}
def list_vocabulary_filters(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "ListVocabularyFilters", input, options)
end
@doc """
Transcribes the audio from a customer service call and applies any additional
Request
Parameters you choose to include in your request.
In addition to many standard transcription features, Call Analytics provides you
with
call characteristics, call summarization, speaker sentiment, and optional
redaction of
your text transcript and your audio file. You can also apply custom categories
to flag
specified conditions. To learn more about these features and insights, refer to
[Analyzing call center audio with Call
Analytics](https://docs.aws.amazon.com/transcribe/latest/dg/call-analytics.html).
If you want to apply categories to your Call Analytics job, you must create them
before submitting your job request. Categories cannot be retroactively applied
to a job.
To create a new category, use the
operation. To learn more about Call Analytics categories, see [Creating categories for post-call
transcriptions](https://docs.aws.amazon.com/transcribe/latest/dg/tca-categories-batch.html)
and [Creating categories for real-time
transcriptions](https://docs.aws.amazon.com/transcribe/latest/dg/tca-categories-stream.html).
To make a `StartCallAnalyticsJob` request, you must first upload your media
file into an Amazon S3 bucket; you can then specify the Amazon S3
location of the file using the `Media` parameter.
Job queuing is available for Call Analytics jobs. If you pass a
`DataAccessRoleArn`
in your request and you exceed your Concurrent Job Limit, your job will
automatically be
added to a queue to be processed once your concurrent job count is below the
limit.
You must include the following parameters in your `StartCallAnalyticsJob`
request:
*
`region`: The Amazon Web Services Region where you are making your
request. For a list of Amazon Web Services Regions supported with Amazon
Transcribe, refer to [Amazon Transcribe endpoints and quotas](https://docs.aws.amazon.com/general/latest/gr/transcribe.html).
*
`CallAnalyticsJobName`: A custom name that you create for your
transcription job that's unique within your Amazon Web Services account.
*
`Media` (`MediaFileUri` or
`RedactedMediaFileUri`): The Amazon S3 location of your
media file.
With Call Analytics, you can redact the audio contained in your media file by
including `RedactedMediaFileUri`, instead of `MediaFileUri`,
to specify the location of your input audio. If you choose to redact your audio,
you
can find your redacted media at the location specified in the
`RedactedMediaFileUri` field of your response.
"""
@spec start_call_analytics_job(map(), start_call_analytics_job_request(), list()) ::
{:ok, start_call_analytics_job_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, start_call_analytics_job_errors()}
def start_call_analytics_job(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "StartCallAnalyticsJob", input, options)
end
@doc """
Transcribes patient-clinician conversations and generates clinical notes.
Amazon Web Services HealthScribe automatically provides rich conversation
transcripts, identifies speaker roles,
classifies dialogues, extracts medical terms, and generates preliminary clinical
notes.
To learn more about these features, refer to [Amazon Web Services HealthScribe](https://docs.aws.amazon.com/transcribe/latest/dg/health-scribe.html).
To make a `StartMedicalScribeJob` request, you must first upload
your media file into an Amazon S3 bucket; you can then specify the Amazon S3
location
of the file using the `Media` parameter.
You must include the following parameters in your
`StartMedicalTranscriptionJob` request:
*
`DataAccessRoleArn`: The ARN of an IAM role with the these minimum permissions:
read permission on input file Amazon S3 bucket specified in `Media`,
write permission on the Amazon S3 bucket specified in `OutputBucketName`, and
full permissions on the KMS key specified in `OutputEncryptionKMSKeyId` (if
set).
The role should also allow `transcribe.amazonaws.com` to assume it.
*
`Media` (`MediaFileUri`): The Amazon S3 location
of your media file.
*
`MedicalScribeJobName`: A custom name you create for your
MedicalScribe job that is unique within your Amazon Web Services account.
*
`OutputBucketName`: The Amazon S3 bucket where you want
your output files stored.
*
`Settings`: A `MedicalScribeSettings` object
that must set exactly one of `ShowSpeakerLabels` or `ChannelIdentification` to
true.
If `ShowSpeakerLabels` is true, `MaxSpeakerLabels` must also be set.
*
`ChannelDefinitions`: A `MedicalScribeChannelDefinitions` array should be set if
and only if the `ChannelIdentification`
value of `Settings` is set to true.
"""
@spec start_medical_scribe_job(map(), start_medical_scribe_job_request(), list()) ::
{:ok, start_medical_scribe_job_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, start_medical_scribe_job_errors()}
def start_medical_scribe_job(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "StartMedicalScribeJob", input, options)
end
@doc """
Transcribes the audio from a medical dictation or conversation and applies any
additional Request Parameters you choose to include in your request.
In addition to many standard transcription features, Amazon Transcribe Medical
provides you with a robust medical vocabulary and, optionally, content
identification,
which adds flags to personal health information (PHI). To learn more about these
features, refer to [How Amazon Transcribe Medical works](https://docs.aws.amazon.com/transcribe/latest/dg/how-it-works-med.html).
To make a `StartMedicalTranscriptionJob` request, you must first upload
your media file into an Amazon S3 bucket; you can then specify the Amazon S3
location
of the file using the `Media` parameter.
You must include the following parameters in your
`StartMedicalTranscriptionJob` request:
*
`region`: The Amazon Web Services Region where you are making your
request. For a list of Amazon Web Services Regions supported with Amazon
Transcribe, refer to [Amazon Transcribe endpoints and quotas](https://docs.aws.amazon.com/general/latest/gr/transcribe.html).
*
`MedicalTranscriptionJobName`: A custom name you create for your
transcription job that is unique within your Amazon Web Services account.
*
`Media` (`MediaFileUri`): The Amazon S3 location
of your media file.
*
`LanguageCode`: This must be `en-US`.
*
`OutputBucketName`: The Amazon S3 bucket where you want
your transcript stored. If you want your output stored in a sub-folder of this
bucket, you must also include `OutputKey`.
*
`Specialty`: This must be `PRIMARYCARE`.
*
`Type`: Choose whether your audio is a conversation or a
dictation.
"""
@spec start_medical_transcription_job(map(), start_medical_transcription_job_request(), list()) ::
{:ok, start_medical_transcription_job_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, start_medical_transcription_job_errors()}
def start_medical_transcription_job(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "StartMedicalTranscriptionJob", input, options)
end
@doc """
Transcribes the audio from a media file and applies any additional Request
Parameters
you choose to include in your request.
To make a `StartTranscriptionJob` request, you must first upload your media
file into an Amazon S3 bucket; you can then specify the Amazon S3
location of the file using the `Media` parameter.
You must include the following parameters in your `StartTranscriptionJob`
request:
*
`region`: The Amazon Web Services Region where you are making your
request. For a list of Amazon Web Services Regions supported with Amazon
Transcribe, refer to [Amazon Transcribe endpoints and quotas](https://docs.aws.amazon.com/general/latest/gr/transcribe.html).
*
`TranscriptionJobName`: A custom name you create for your
transcription job that is unique within your Amazon Web Services account.
*
`Media` (`MediaFileUri`): The Amazon S3 location
of your media file.
*
One of `LanguageCode`, `IdentifyLanguage`, or
`IdentifyMultipleLanguages`: If you know the language of your
media file, specify it using the `LanguageCode` parameter; you can
find all valid language codes in the [Supported languages](https://docs.aws.amazon.com/transcribe/latest/dg/supported-languages.html)
table. If you do not know the languages spoken in your
media, use either `IdentifyLanguage` or
`IdentifyMultipleLanguages` and let Amazon Transcribe identify
the languages for you.
"""
@spec start_transcription_job(map(), start_transcription_job_request(), list()) ::
{:ok, start_transcription_job_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, start_transcription_job_errors()}
def start_transcription_job(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "StartTranscriptionJob", input, options)
end
@doc """
Adds one or more custom tags, each in the form of a key:value pair, to the
specified
resource.
To learn more about using tags with Amazon Transcribe, refer to [Tagging resources](https://docs.aws.amazon.com/transcribe/latest/dg/tagging.html).
"""
@spec tag_resource(map(), tag_resource_request(), list()) ::
{:ok, tag_resource_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, tag_resource_errors()}
def tag_resource(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "TagResource", input, options)
end
@doc """
Removes the specified tags from the specified Amazon Transcribe resource.
If you include `UntagResource` in your request, you must also include
`ResourceArn` and `TagKeys`.
"""
@spec untag_resource(map(), untag_resource_request(), list()) ::
{:ok, untag_resource_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, untag_resource_errors()}
def untag_resource(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "UntagResource", input, options)
end
@doc """
Updates the specified Call Analytics category with new rules.
Note that the
`UpdateCallAnalyticsCategory` operation overwrites all existing rules
contained in the specified category. You cannot append additional rules onto an
existing
category.
To create a new category, see .
"""
@spec update_call_analytics_category(map(), update_call_analytics_category_request(), list()) ::
{:ok, update_call_analytics_category_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, update_call_analytics_category_errors()}
def update_call_analytics_category(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "UpdateCallAnalyticsCategory", input, options)
end
@doc """
Updates an existing custom medical vocabulary with new values.
This operation
overwrites all existing information with your new values; you cannot append new
terms
onto an existing custom vocabulary.
"""
@spec update_medical_vocabulary(map(), update_medical_vocabulary_request(), list()) ::
{:ok, update_medical_vocabulary_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, update_medical_vocabulary_errors()}
def update_medical_vocabulary(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "UpdateMedicalVocabulary", input, options)
end
@doc """
Updates an existing custom vocabulary with new values.
This operation overwrites all
existing information with your new values; you cannot append new terms onto an
existing
custom vocabulary.
"""
@spec update_vocabulary(map(), update_vocabulary_request(), list()) ::
{:ok, update_vocabulary_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, update_vocabulary_errors()}
def update_vocabulary(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "UpdateVocabulary", input, options)
end
@doc """
Updates an existing custom vocabulary filter with a new list of words.
The new list
you provide overwrites all previous entries; you cannot append new terms onto an
existing custom vocabulary filter.
"""
@spec update_vocabulary_filter(map(), update_vocabulary_filter_request(), list()) ::
{:ok, update_vocabulary_filter_response(), any()}
| {:error, {:unexpected_response, any()}}
| {:error, term()}
| {:error, update_vocabulary_filter_errors()}
def update_vocabulary_filter(%Client{} = client, input, options \\ []) do
meta = metadata()
Request.request_post(client, meta, "UpdateVocabularyFilter", input, options)
end
end
