Module types

Source
Expand description

Data structures used by operation inputs/outputs.

Modules§

builders
Builders
error
Error types that Amazon Transcribe Service can respond with.

Structs§

AbsoluteTimeRange

A time range, in milliseconds, between two points in your media file.

You can use StartTime and EndTime to search a custom segment. For example, setting StartTime to 10000 and EndTime to 50000 only searches for your specified criteria in the audio contained between the 10,000 millisecond mark and the 50,000 millisecond mark of your media file. You must use StartTime and EndTime as a set; that is, if you include one, you must include both.

You can use also First to search from the start of the audio until the time that you specify, or Last to search from the time that you specify until the end of the audio. For example, setting First to 50000 only searches for your specified criteria in the audio contained between the start of the media file to the 50,000 millisecond mark. You can use First and Last independently of each other.

If you prefer to use percentage instead of milliseconds, see .

CallAnalyticsJob

Provides detailed information about a 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 the RedactedMediaFileUri field of your response.

CallAnalyticsJobDetails

Contains details about a call analytics job, including information about skipped analytics features.

CallAnalyticsJobSettings

Provides additional optional settings for your request, including content redaction, automatic language identification; allows you to apply custom language models, custom vocabulary filters, and custom vocabularies.

CallAnalyticsJobSummary

Provides detailed information about a specific Call Analytics job.

CallAnalyticsSkippedFeature

Represents a skipped analytics feature during the analysis of a call analytics job.

The Feature field indicates the type of analytics feature that was skipped.

The Message field contains additional information or a message explaining why the analytics feature was skipped.

The ReasonCode field provides a code indicating the reason why the analytics feature was skipped.

CategoryProperties

Provides you with the properties of the Call Analytics category you specified in your request. This includes the list of rules that define the specified category.

ChannelDefinition

Makes it possible to specify which speaker is on which channel. For example, if your agent is the first participant to speak, you would set ChannelId to 0 (to indicate the first channel) and ParticipantRole to AGENT (to indicate that it's the agent speaking).

ClinicalNoteGenerationSettings

The output configuration for clinical note generation.

ContentRedaction

Makes it possible to redact or flag specified personally identifiable information (PII) in your transcript. If you use ContentRedaction, you must also include the sub-parameters: RedactionOutput and RedactionType. You can optionally include PiiEntityTypes to choose which types of PII you want to redact.

InputDataConfig

Contains the Amazon S3 location of the training data you want to use to create a new custom language model, and permissions to access this location.

When using InputDataConfig, you must include these sub-parameters: S3Uri and DataAccessRoleArn. You can optionally include TuningDataS3Uri.

InterruptionFilter

Flag the presence or absence of interruptions in your Call Analytics transcription output.

Rules using InterruptionFilter are designed to match:

  • Instances where an agent interrupts a customer

  • Instances where a customer interrupts an agent

  • Either participant interrupting the other

  • A lack of interruptions

See Rule criteria for post-call categories for usage examples.

JobExecutionSettings

Makes it possible to control how your transcription job is processed. Currently, the only JobExecutionSettings modification you can choose is enabling job queueing using the AllowDeferredExecution sub-parameter.

If you include JobExecutionSettings in your request, you must also include the sub-parameters: AllowDeferredExecution and DataAccessRoleArn.

LanguageCodeItem

Provides information on the speech contained in a discreet utterance when multi-language identification is enabled in your request. This utterance represents a block of speech consisting of one language, preceded or followed by a block of speech in a different language.

LanguageIdSettings

If using automatic language identification in your request and you want to apply a custom language model, a custom vocabulary, or a custom vocabulary filter, include LanguageIdSettings with the relevant sub-parameters (VocabularyName, LanguageModelName, and VocabularyFilterName). Note that multi-language identification (IdentifyMultipleLanguages) doesn't support custom language models.

LanguageIdSettings supports two to five language codes. Each language code you include can have an associated custom language model, custom vocabulary, and custom vocabulary filter. The language codes that you specify must match the languages of the associated custom language models, custom vocabularies, and custom vocabulary filters.

It's recommended that you include LanguageOptions when using LanguageIdSettings to ensure that the correct language dialect is identified. For example, if you specify a custom vocabulary that is in en-US but Amazon Transcribe determines that the language spoken in your media is en-AU, your custom vocabulary is not applied to your transcription. If you include LanguageOptions and include en-US as the only English language dialect, your custom vocabulary is applied to your transcription.

If you want to include a custom language model with your request but do not want to use automatic language identification, use instead the parameter with the LanguageModelName sub-parameter. If you want to include a custom vocabulary or a custom vocabulary filter (or both) with your request but do not want to use automatic language identification, use instead the parameter with the VocabularyName or VocabularyFilterName (or both) sub-parameter.

LanguageModel

Provides information about a custom language model, including:

  • The base model name

  • When the model was created

  • The location of the files used to train the model

  • When the model was last modified

  • The name you chose for the model

  • The model's language

  • The model's processing state

  • Any available upgrades for the base model

Media

Describes the Amazon S3 location of the media file you want to use in your request.

For information on supported media formats, refer to the MediaFormat parameter or the Media formats section in the Amazon S3 Developer Guide.

MedicalScribeChannelDefinition

Indicates which speaker is on which channel. The options are CLINICIAN and PATIENT

MedicalScribeJob

Provides detailed information about a Medical Scribe job.

To view the status of the specified Medical Scribe job, check the MedicalScribeJobStatus field. If the status is COMPLETED, the job is finished and you can find the results at the locations specified in MedicalScribeOutput. If the status is FAILED, FailureReason provides details on why your Medical Scribe job failed.

MedicalScribeJobSummary

Provides detailed information about a specific Medical Scribe job.

MedicalScribeOutput

The location of the output of your Medical Scribe job. ClinicalDocumentUri holds the Amazon S3 URI for the Clinical Document and TranscriptFileUri holds the Amazon S3 URI for the Transcript.

MedicalScribeSettings

Makes it possible to control how your Medical Scribe job is processed using a MedicalScribeSettings object. Specify ChannelIdentification if ChannelDefinitions are set. Enabled ShowSpeakerLabels if ChannelIdentification and ChannelDefinitions are not set. One and only one of ChannelIdentification and ShowSpeakerLabels must be set. If ShowSpeakerLabels is set, MaxSpeakerLabels must also be set. Use Settings to specify a vocabulary or vocabulary filter or both using VocabularyName, VocabularyFilterName. VocabularyFilterMethod must be specified if VocabularyFilterName is set.

MedicalTranscript

Provides you with the Amazon S3 URI you can use to access your transcript.

MedicalTranscriptionJob

Provides detailed information about a 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 and 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.

MedicalTranscriptionJobSummary

Provides detailed information about a specific medical transcription job.

MedicalTranscriptionSetting

Allows additional optional settings in your request, including channel identification, alternative transcriptions, and speaker partitioning. You can use that to apply custom vocabularies to your medical transcription job.

ModelSettings

Provides the name of the custom language model that was included in the specified transcription job.

Only use ModelSettings with the LanguageModelName sub-parameter if you're not using automatic language identification (). If using LanguageIdSettings in your request, this parameter contains a LanguageModelName sub-parameter.

NonTalkTimeFilter

Flag the presence or absence of periods of silence in your Call Analytics transcription output.

Rules using NonTalkTimeFilter are designed to match:

  • The presence of silence at specified periods throughout the call

  • The presence of speech at specified periods throughout the call

See Rule criteria for post-call categories for usage examples.

RelativeTimeRange

A time range, in percentage, between two points in your media file.

You can use StartPercentage and EndPercentage to search a custom segment. For example, setting StartPercentage to 10 and EndPercentage to 50 only searches for your specified criteria in the audio contained between the 10 percent mark and the 50 percent mark of your media file.

You can use also First to search from the start of the media file until the time that you specify. Or use Last to search from the time that you specify until the end of the media file. For example, setting First to 10 only searches for your specified criteria in the audio contained in the first 10 percent of the media file.

If you prefer to use milliseconds instead of percentage, see .

SentimentFilter

Flag the presence or absence of specific sentiments detected in your Call Analytics transcription output.

Rules using SentimentFilter are designed to match:

  • The presence or absence of a positive sentiment felt by the customer, agent, or both at specified points in the call

  • The presence or absence of a negative sentiment felt by the customer, agent, or both at specified points in the call

  • The presence or absence of a neutral sentiment felt by the customer, agent, or both at specified points in the call

  • The presence or absence of a mixed sentiment felt by the customer, the agent, or both at specified points in the call

See Rule criteria for post-call categories for usage examples.

Settings

Allows additional optional settings in your request, including channel identification, alternative transcriptions, and speaker partitioning. You can use that to apply custom vocabularies to your transcription job.

Subtitles

Generate subtitles for your media file with your transcription request.

You can choose a start index of 0 or 1, and you can specify either WebVTT or SubRip (or both) as your output format.

Note that your subtitle files are placed in the same location as your transcription output.

SubtitlesOutput

Provides information about your subtitle file, including format, start index, and Amazon S3 location.

Summarization

Contains GenerateAbstractiveSummary, which is a required parameter if you want to enable Generative call summarization in your Call Analytics request.

Tag

Adds metadata, in the form of a key:value pair, to the specified resource.

For example, you could add the tag Department:Sales to a resource to indicate that it pertains to your organization's sales department. You can also use tags for tag-based access control.

To learn more about tagging, see Tagging resources.

ToxicityDetectionSettings

Contains ToxicityCategories, which is a required parameter if you want to enable toxicity detection (ToxicityDetection) in your transcription request.

Transcript

Provides you with the Amazon S3 URI you can use to access your transcript.

TranscriptFilter

Flag the presence or absence of specific words or phrases detected in your Call Analytics transcription output.

Rules using TranscriptFilter are designed to match:

  • Custom words or phrases spoken by the agent, the customer, or both

  • Custom words or phrases not spoken by the agent, the customer, or either

  • Custom words or phrases that occur at a specific time frame

See Rule criteria for post-call categories and Rule criteria for streaming categories for usage examples.

TranscriptionJob

Provides detailed information about a transcription job.

To view the status of the specified transcription job, check the TranscriptionJobStatus field. If the status is COMPLETED, the job is finished and 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.

TranscriptionJobSummary

Provides detailed information about a specific transcription job.

VocabularyFilterInfo

Provides information about a custom vocabulary filter, including the language of the filter, when it was last modified, and its name.

VocabularyInfo

Provides information about a custom vocabulary, including the language of the custom vocabulary, when it was last modified, its name, and the processing state.

Enums§

BaseModelName
When writing a match expression against BaseModelName, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
CallAnalyticsFeature
When writing a match expression against CallAnalyticsFeature, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
CallAnalyticsJobStatus
When writing a match expression against CallAnalyticsJobStatus, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
CallAnalyticsSkippedReasonCode
When writing a match expression against CallAnalyticsSkippedReasonCode, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
ClmLanguageCode
When writing a match expression against ClmLanguageCode, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
InputType
When writing a match expression against InputType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
LanguageCode
When writing a match expression against LanguageCode, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
MediaFormat
When writing a match expression against MediaFormat, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
MedicalContentIdentificationType
When writing a match expression against MedicalContentIdentificationType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
MedicalScribeJobStatus
When writing a match expression against MedicalScribeJobStatus, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
MedicalScribeLanguageCode
When writing a match expression against MedicalScribeLanguageCode, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
MedicalScribeNoteTemplate
When writing a match expression against MedicalScribeNoteTemplate, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
MedicalScribeParticipantRole
When writing a match expression against MedicalScribeParticipantRole, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
ModelStatus
When writing a match expression against ModelStatus, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
OutputLocationType
When writing a match expression against OutputLocationType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
ParticipantRole
When writing a match expression against ParticipantRole, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
PiiEntityType
When writing a match expression against PiiEntityType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
RedactionOutput
When writing a match expression against RedactionOutput, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
RedactionType
When writing a match expression against RedactionType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
Rule

A rule is a set of criteria that you can specify to flag an attribute in your Call Analytics output. Rules define a Call Analytics category.

Rules can include these parameters: , , , and .

To learn more about Call Analytics rules and categories, see Creating categories for post-call transcriptions and Creating categories for real-time transcriptions.

To learn more about Call Analytics, see Analyzing call center audio with Call Analytics.

SentimentValue
When writing a match expression against SentimentValue, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
Specialty
When writing a match expression against Specialty, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
SubtitleFormat
When writing a match expression against SubtitleFormat, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
ToxicityCategory
When writing a match expression against ToxicityCategory, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
TranscriptFilterType
When writing a match expression against TranscriptFilterType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
TranscriptionJobStatus
When writing a match expression against TranscriptionJobStatus, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
Type
When writing a match expression against Type, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
VocabularyFilterMethod
When writing a match expression against VocabularyFilterMethod, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
VocabularyState
When writing a match expression against VocabularyState, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.