Struct aws_sdk_transcribestreaming::client::Client

pub struct Client { /* private fields */ }

Client for Amazon Transcribe Streaming Service

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

Constructing a Client

A Config is required to construct a client. For most use cases, the aws-config crate should be used to automatically resolve this config using aws_config::load_from_env(), since this will resolve an SdkConfig which can be shared across multiple different AWS SDK clients. This config resolution process can be customized by calling aws_config::from_env() instead, which returns a ConfigLoader that uses the builder pattern to customize the default config.

In the simplest case, creating a client looks as follows:

let config = aws_config::load_from_env().await;
let client = aws_sdk_transcribestreaming::Client::new(&config);

Occasionally, SDKs may have additional service-specific values that can be set on the Config that is absent from SdkConfig, or slightly different settings for a specific client may be desired. The Builder struct implements From<&SdkConfig>, so setting these specific settings can be done as follows:

let sdk_config = ::aws_config::load_from_env().await;
let config = aws_sdk_transcribestreaming::config::Builder::from(&sdk_config)
    .some_service_specific_setting("value")
    .build();

See the aws-config docs and Config for more information on customizing configuration.

Note: Client construction is expensive due to connection thread pool initialization, and should be done once at application start-up.

Using the Client

A client has a function for every operation that can be performed by the service. For example, the StartCallAnalyticsStreamTranscription operation has a Client::start_call_analytics_stream_transcription, function which returns a builder for that operation. The fluent builder ultimately has a send() function that returns an async future that returns a result, as illustrated below:

let result = client.start_call_analytics_stream_transcription()
    .language_code("example")
    .send()
    .await;

The underlying HTTP requests that get made by this can be modified with the customize_operation function on the fluent builder. See the customize module for more information.

Implementations

impl Client

pub fn start_call_analytics_stream_transcription( &self, ) -> StartCallAnalyticsStreamTranscriptionFluentBuilder

Constructs a fluent builder for the StartCallAnalyticsStreamTranscription operation.

• The fluent builder is configurable:
  • language_code(CallAnalyticsLanguageCode) / set_language_code(Option<CallAnalyticsLanguageCode>):
    required: true
    

    Specify the language code that represents the language spoken in your audio.

    If you’re unsure of the language spoken in your audio, consider using IdentifyLanguage to enable automatic language identification.

    For a list of languages supported with streaming Call Analytics, refer to the Supported languages table.

    
    
  • media_sample_rate_hertz(i32) / set_media_sample_rate_hertz(Option<i32>):
    required: true
    

    The sample rate of the input audio (in hertz). Low-quality audio, such as telephone audio, is typically around 8,000 Hz. High-quality audio typically ranges from 16,000 Hz to 48,000 Hz. Note that the sample rate you specify must match that of your audio.

    
    
  • media_encoding(MediaEncoding) / set_media_encoding(Option<MediaEncoding>):
    required: true
    

    Specify the encoding of your input audio. Supported formats are:

    • FLAC

    • OPUS-encoded audio in an Ogg container

    • PCM (only signed 16-bit little-endian audio formats, which does not include WAV)

    For more information, see Media formats.

    
    
  • vocabulary_name(impl Into<String>) / set_vocabulary_name(Option<String>):
    required: false
    

    Specify the name of the custom vocabulary that you want to use when processing your transcription. Note that vocabulary names are case sensitive.

    If the language of the specified custom vocabulary doesn’t match the language identified in your media, the custom vocabulary is not applied to your transcription.

    For more information, see Custom vocabularies.

    
    
  • session_id(impl Into<String>) / set_session_id(Option<String>):
    required: false
    

    Specify a name for your Call Analytics transcription session. If you don’t include this parameter in your request, Amazon Transcribe generates an ID and returns it in the response.

    You can use a session ID to retry a streaming session.

    
    
  • audio_stream(EventStreamSender<AudioStream, AudioStreamError>) / set_audio_stream(EventStreamSender<AudioStream, AudioStreamError>):
    required: true
    

    An encoded stream of audio blobs. Audio streams are encoded as either HTTP/2 or WebSocket data frames.

    For more information, see Transcribing streaming audio.

    
    
  • vocabulary_filter_name(impl Into<String>) / set_vocabulary_filter_name(Option<String>):
    required: false
    

    Specify the name of the custom vocabulary filter that you want to use when processing your transcription. Note that vocabulary filter names are case sensitive.

    If the language of the specified custom vocabulary filter doesn’t match the language identified in your media, the vocabulary filter is not applied to your transcription.

    For more information, see Using vocabulary filtering with unwanted words.

    
    
  • vocabulary_filter_method(VocabularyFilterMethod) / set_vocabulary_filter_method(Option<VocabularyFilterMethod>):
    required: false
    

    Specify how you want your vocabulary filter applied to your transcript.

    To replace words with ***, choose mask.

    To delete words, choose remove.

    To flag words without changing them, choose tag.

    
    
  • language_model_name(impl Into<String>) / set_language_model_name(Option<String>):
    required: false
    

    Specify the name of the custom language model that you want to use when processing your transcription. Note that language model names are case sensitive.

    The language of the specified language model must match the language code you specify in your transcription request. If the languages don’t match, the custom language model isn’t applied. There are no errors or warnings associated with a language mismatch.

    For more information, see Custom language models.

    
    
  • enable_partial_results_stabilization(bool) / set_enable_partial_results_stabilization(Option<bool>):
    required: false
    

    Enables partial result stabilization for your transcription. Partial result stabilization can reduce latency in your output, but may impact accuracy. For more information, see Partial-result stabilization.

    
    
  • partial_results_stability(PartialResultsStability) / set_partial_results_stability(Option<PartialResultsStability>):
    required: false
    

    Specify the level of stability to use when you enable partial results stabilization (EnablePartialResultsStabilization).

    Low stability provides the highest accuracy. High stability transcribes faster, but with slightly lower accuracy.

    For more information, see Partial-result stabilization.

    
    
  • content_identification_type(ContentIdentificationType) / set_content_identification_type(Option<ContentIdentificationType>):
    required: false
    

    Labels all personally identifiable information (PII) identified in your transcript.

    Content identification is performed at the segment level; PII specified in PiiEntityTypes is flagged upon complete transcription of an audio segment.

    You can’t set ContentIdentificationType and ContentRedactionType in the same request. If you set both, your request returns a BadRequestException.

    For more information, see Redacting or identifying personally identifiable information.

    
    
  • content_redaction_type(ContentRedactionType) / set_content_redaction_type(Option<ContentRedactionType>):
    required: false
    

    Redacts all personally identifiable information (PII) identified in your transcript.

    Content redaction is performed at the segment level; PII specified in PiiEntityTypes is redacted upon complete transcription of an audio segment.

    You can’t set ContentRedactionType and ContentIdentificationType in the same request. If you set both, your request returns a BadRequestException.

    For more information, see Redacting or identifying personally identifiable information.

    
    
  • pii_entity_types(impl Into<String>) / set_pii_entity_types(Option<String>):
    required: false
    

    Specify which types of personally identifiable information (PII) you want to redact in your transcript. You can include as many types as you’d like, or you can select ALL.

    To include PiiEntityTypes in your Call Analytics request, you must also include either ContentIdentificationType or ContentRedactionType.

    Values must be comma-separated and can include: BANK_ACCOUNT_NUMBER, BANK_ROUTING, CREDIT_DEBIT_NUMBER, CREDIT_DEBIT_CVV, CREDIT_DEBIT_EXPIRY, PIN, EMAIL, ADDRESS, NAME, PHONE, SSN, or ALL.

    
    
• On success, responds with StartCallAnalyticsStreamTranscriptionOutput with field(s):
  • request_id(Option<String>):

    Provides the identifier for your Call Analytics streaming request.

  • language_code(Option<CallAnalyticsLanguageCode>):

    Provides the language code that you specified in your Call Analytics request.

  • media_sample_rate_hertz(Option<i32>):

    Provides the sample rate that you specified in your Call Analytics request.

  • media_encoding(Option<MediaEncoding>):

    Provides the media encoding you specified in your Call Analytics request.

  • vocabulary_name(Option<String>):

    Provides the name of the custom vocabulary that you specified in your Call Analytics request.

  • session_id(Option<String>):

    Provides the identifier for your Call Analytics transcription session.

  • call_analytics_transcript_result_stream(EventReceiver<CallAnalyticsTranscriptResultStream, CallAnalyticsTranscriptResultStreamError>):

    Provides detailed information about your Call Analytics streaming session.

  • vocabulary_filter_name(Option<String>):

    Provides the name of the custom vocabulary filter that you specified in your Call Analytics request.

  • vocabulary_filter_method(Option<VocabularyFilterMethod>):

    Provides the vocabulary filtering method used in your Call Analytics transcription.

  • language_model_name(Option<String>):

    Provides the name of the custom language model that you specified in your Call Analytics request.

  • enable_partial_results_stabilization(bool):

    Shows whether partial results stabilization was enabled for your Call Analytics transcription.

  • partial_results_stability(Option<PartialResultsStability>):

    Provides the stabilization level used for your transcription.

  • content_identification_type(Option<ContentIdentificationType>):

    Shows whether content identification was enabled for your Call Analytics transcription.

  • content_redaction_type(Option<ContentRedactionType>):

    Shows whether content redaction was enabled for your Call Analytics transcription.

  • pii_entity_types(Option<String>):

    Lists the PII entity types you specified in your Call Analytics request.

• On failure, responds with SdkError<StartCallAnalyticsStreamTranscriptionError>

impl Client

pub fn start_medical_stream_transcription( &self, ) -> StartMedicalStreamTranscriptionFluentBuilder

Constructs a fluent builder for the StartMedicalStreamTranscription operation.

• The fluent builder is configurable:
  • language_code(LanguageCode) / set_language_code(Option<LanguageCode>):
    required: true
    

    Specify the language code that represents the language spoken in your audio.

    Amazon Transcribe Medical only supports US English (en-US).

    
    
  • media_sample_rate_hertz(i32) / set_media_sample_rate_hertz(Option<i32>):
    required: true
    

    The sample rate of the input audio (in hertz). Amazon Transcribe Medical supports a range from 16,000 Hz to 48,000 Hz. Note that the sample rate you specify must match that of your audio.

    
    
  • media_encoding(MediaEncoding) / set_media_encoding(Option<MediaEncoding>):
    required: true
    

    Specify the encoding used for the input audio. Supported formats are:

    • FLAC

    • OPUS-encoded audio in an Ogg container

    • PCM (only signed 16-bit little-endian audio formats, which does not include WAV)

    For more information, see Media formats.

    
    
  • vocabulary_name(impl Into<String>) / set_vocabulary_name(Option<String>):
    required: false
    

    Specify the name of the custom vocabulary that you want to use when processing your transcription. Note that vocabulary names are case sensitive.

    
    
  • specialty(Specialty) / set_specialty(Option<Specialty>):
    required: true
    

    Specify the medical specialty contained in your audio.

    
    
  • r#type(Type) / set_type(Option<Type>):
    required: true
    

    Specify the type of input audio. For example, choose DICTATION for a provider dictating patient notes and CONVERSATION for a dialogue between a patient and a medical professional.

    
    
  • show_speaker_label(bool) / set_show_speaker_label(Option<bool>):
    required: false
    

    Enables speaker partitioning (diarization) in your transcription output. Speaker partitioning labels the speech from individual speakers in your media file.

    For more information, see Partitioning speakers (diarization).

    
    
  • session_id(impl Into<String>) / set_session_id(Option<String>):
    required: false
    

    Specify a name for your transcription session. If you don’t include this parameter in your request, Amazon Transcribe Medical generates an ID and returns it in the response.

    You can use a session ID to retry a streaming session.

    
    
  • audio_stream(EventStreamSender<AudioStream, AudioStreamError>) / set_audio_stream(EventStreamSender<AudioStream, AudioStreamError>):
    required: true
    

    An encoded stream of audio blobs. Audio streams are encoded as either HTTP/2 or WebSocket data frames.

    For more information, see Transcribing streaming audio.

    
    
  • enable_channel_identification(bool) / set_enable_channel_identification(Option<bool>):
    required: false
    

    Enables channel identification in multi-channel audio.

    Channel identification transcribes the audio on each channel independently, then appends the output for each channel into one transcript.

    If you have multi-channel audio and do not enable channel identification, your audio is transcribed in a continuous manner and your transcript is not separated by channel.

    For more information, see Transcribing multi-channel audio.

    
    
  • number_of_channels(i32) / set_number_of_channels(Option<i32>):
    required: false
    

    Specify the number of channels in your audio stream. Up to two channels are supported.

    
    
  • content_identification_type(MedicalContentIdentificationType) / set_content_identification_type(Option<MedicalContentIdentificationType>):
    required: false
    

    Labels all personal health information (PHI) identified in your transcript.

    Content identification is performed at the segment level; PHI is flagged upon complete transcription of an audio segment.

    For more information, see Identifying personal health information (PHI) in a transcription.

    
    
• On success, responds with StartMedicalStreamTranscriptionOutput with field(s):
  • request_id(Option<String>):

    Provides the identifier for your streaming request.

  • language_code(Option<LanguageCode>):

    Provides the language code that you specified in your request. This must be en-US.

  • media_sample_rate_hertz(Option<i32>):

    Provides the sample rate that you specified in your request.

  • media_encoding(Option<MediaEncoding>):

    Provides the media encoding you specified in your request.

  • vocabulary_name(Option<String>):

    Provides the name of the custom vocabulary that you specified in your request.

  • specialty(Option<Specialty>):

    Provides the medical specialty that you specified in your request.

  • r#type(Option<Type>):

    Provides the type of audio you specified in your request.

  • show_speaker_label(bool):

    Shows whether speaker partitioning was enabled for your transcription.

  • session_id(Option<String>):

    Provides the identifier for your transcription session.

  • transcript_result_stream(EventReceiver<MedicalTranscriptResultStream, MedicalTranscriptResultStreamError>):

    Provides detailed information about your streaming session.

  • enable_channel_identification(bool):

    Shows whether channel identification was enabled for your transcription.

  • number_of_channels(Option<i32>):

    Provides the number of channels that you specified in your request.

  • content_identification_type(Option<MedicalContentIdentificationType>):

    Shows whether content identification was enabled for your transcription.

• On failure, responds with SdkError<StartMedicalStreamTranscriptionError>

impl Client

pub fn start_stream_transcription( &self, ) -> StartStreamTranscriptionFluentBuilder

Constructs a fluent builder for the StartStreamTranscription operation.

• The fluent builder is configurable:
  • language_code(LanguageCode) / set_language_code(Option<LanguageCode>):
    required: false
    

    Specify the language code that represents the language spoken in your audio.

    If you’re unsure of the language spoken in your audio, consider using IdentifyLanguage to enable automatic language identification.

    For a list of languages supported with Amazon Transcribe streaming, refer to the Supported languages table.

    
    
  • media_sample_rate_hertz(i32) / set_media_sample_rate_hertz(Option<i32>):
    required: true
    

    The sample rate of the input audio (in hertz). Low-quality audio, such as telephone audio, is typically around 8,000 Hz. High-quality audio typically ranges from 16,000 Hz to 48,000 Hz. Note that the sample rate you specify must match that of your audio.

    
    
  • media_encoding(MediaEncoding) / set_media_encoding(Option<MediaEncoding>):
    required: true
    

    Specify the encoding of your input audio. Supported formats are:

    • FLAC

    • OPUS-encoded audio in an Ogg container

    • PCM (only signed 16-bit little-endian audio formats, which does not include WAV)

    For more information, see Media formats.

    
    
  • vocabulary_name(impl Into<String>) / set_vocabulary_name(Option<String>):
    required: false
    

    Specify the name of the custom vocabulary that you want to use when processing your transcription. Note that vocabulary names are case sensitive.

    If the language of the specified custom vocabulary doesn’t match the language identified in your media, the custom vocabulary is not applied to your transcription.

    This parameter is not intended for use with the IdentifyLanguage parameter. If you’re including IdentifyLanguage in your request and want to use one or more custom vocabularies with your transcription, use the VocabularyNames parameter instead.

    For more information, see Custom vocabularies.

    
    
  • session_id(impl Into<String>) / set_session_id(Option<String>):
    required: false
    

    Specify a name for your transcription session. If you don’t include this parameter in your request, Amazon Transcribe generates an ID and returns it in the response.

    You can use a session ID to retry a streaming session.

    
    
  • audio_stream(EventStreamSender<AudioStream, AudioStreamError>) / set_audio_stream(EventStreamSender<AudioStream, AudioStreamError>):
    required: true
    

    An encoded stream of audio blobs. Audio streams are encoded as either HTTP/2 or WebSocket data frames.

    For more information, see Transcribing streaming audio.

    
    
  • vocabulary_filter_name(impl Into<String>) / set_vocabulary_filter_name(Option<String>):
    required: false
    

    Specify the name of the custom vocabulary filter that you want to use when processing your transcription. Note that vocabulary filter names are case sensitive.

    If the language of the specified custom vocabulary filter doesn’t match the language identified in your media, the vocabulary filter is not applied to your transcription.

    This parameter is not intended for use with the IdentifyLanguage parameter. If you’re including IdentifyLanguage in your request and want to use one or more vocabulary filters with your transcription, use the VocabularyFilterNames parameter instead.

    For more information, see Using vocabulary filtering with unwanted words.

    
    
  • vocabulary_filter_method(VocabularyFilterMethod) / set_vocabulary_filter_method(Option<VocabularyFilterMethod>):
    required: false
    

    Specify how you want your vocabulary filter applied to your transcript.

    To replace words with ***, choose mask.

    To delete words, choose remove.

    To flag words without changing them, choose tag.

    
    
  • show_speaker_label(bool) / set_show_speaker_label(Option<bool>):
    required: false
    

    Enables speaker partitioning (diarization) in your transcription output. Speaker partitioning labels the speech from individual speakers in your media file.

    For more information, see Partitioning speakers (diarization).

    
    
  • enable_channel_identification(bool) / set_enable_channel_identification(Option<bool>):
    required: false
    

    Enables channel identification in multi-channel audio.

    Channel identification transcribes the audio on each channel independently, then appends the output for each channel into one transcript.

    If you have multi-channel audio and do not enable channel identification, your audio is transcribed in a continuous manner and your transcript is not separated by channel.

    For more information, see Transcribing multi-channel audio.

    
    
  • number_of_channels(i32) / set_number_of_channels(Option<i32>):
    required: false
    

    Specify the number of channels in your audio stream. Up to two channels are supported.

    
    
  • enable_partial_results_stabilization(bool) / set_enable_partial_results_stabilization(Option<bool>):
    required: false
    

    Enables partial result stabilization for your transcription. Partial result stabilization can reduce latency in your output, but may impact accuracy. For more information, see Partial-result stabilization.

    
    
  • partial_results_stability(PartialResultsStability) / set_partial_results_stability(Option<PartialResultsStability>):
    required: false
    

    Specify the level of stability to use when you enable partial results stabilization (EnablePartialResultsStabilization).

    Low stability provides the highest accuracy. High stability transcribes faster, but with slightly lower accuracy.

    For more information, see Partial-result stabilization.

    
    
  • content_identification_type(ContentIdentificationType) / set_content_identification_type(Option<ContentIdentificationType>):
    required: false
    

    Labels all personally identifiable information (PII) identified in your transcript.

    Content identification is performed at the segment level; PII specified in PiiEntityTypes is flagged upon complete transcription of an audio segment.

    You can’t set ContentIdentificationType and ContentRedactionType in the same request. If you set both, your request returns a BadRequestException.

    For more information, see Redacting or identifying personally identifiable information.

    
    
  • content_redaction_type(ContentRedactionType) / set_content_redaction_type(Option<ContentRedactionType>):
    required: false
    

    Redacts all personally identifiable information (PII) identified in your transcript.

    Content redaction is performed at the segment level; PII specified in PiiEntityTypes is redacted upon complete transcription of an audio segment.

    You can’t set ContentRedactionType and ContentIdentificationType in the same request. If you set both, your request returns a BadRequestException.

    For more information, see Redacting or identifying personally identifiable information.

    
    
  • pii_entity_types(impl Into<String>) / set_pii_entity_types(Option<String>):
    required: false
    

    Specify which types of personally identifiable information (PII) you want to redact in your transcript. You can include as many types as you’d like, or you can select ALL.

    To include PiiEntityTypes in your request, you must also include either ContentIdentificationType or ContentRedactionType.

    Values must be comma-separated and can include: BANK_ACCOUNT_NUMBER, BANK_ROUTING, CREDIT_DEBIT_NUMBER, CREDIT_DEBIT_CVV, CREDIT_DEBIT_EXPIRY, PIN, EMAIL, ADDRESS, NAME, PHONE, SSN, or ALL.

    
    
  • language_model_name(impl Into<String>) / set_language_model_name(Option<String>):
    required: false
    

    Specify the name of the custom language model that you want to use when processing your transcription. Note that language model names are case sensitive.

    The language of the specified language model must match the language code you specify in your transcription request. If the languages don’t match, the custom language model isn’t applied. There are no errors or warnings associated with a language mismatch.

    For more information, see Custom language models.

    
    
  • identify_language(bool) / set_identify_language(Option<bool>):
    required: false
    

    Enables automatic language identification for your transcription.

    If you include IdentifyLanguage, you can optionally include a list of language codes, using LanguageOptions, that you think may be present in your audio stream. Including language options can improve transcription accuracy.

    You can also include a preferred language using PreferredLanguage. Adding a preferred language can help Amazon Transcribe identify the language faster than if you omit this parameter.

    If you have multi-channel audio that contains different languages on each channel, and you’ve enabled channel identification, automatic language identification identifies the dominant language on each audio channel.

    Note that you must include either LanguageCode or IdentifyLanguage or IdentifyMultipleLanguages in your request. If you include more than one of these parameters, your transcription job fails.

    Streaming language identification can’t be combined with custom language models or redaction.

    
    
  • language_options(impl Into<String>) / set_language_options(Option<String>):
    required: false
    

    Specify two or more language codes that represent the languages you think may be present in your media; including more than five is not recommended. If you’re unsure what languages are present, do not include this parameter.

    Including language options can improve the accuracy of language identification.

    If you include LanguageOptions in your request, you must also include IdentifyLanguage.

    For a list of languages supported with Amazon Transcribe streaming, refer to the Supported languages table.

    You can only include one language dialect per language per stream. For example, you cannot include en-US and en-AU in the same request.

    
    
  • preferred_language(LanguageCode) / set_preferred_language(Option<LanguageCode>):
    required: false
    

    Specify a preferred language from the subset of languages codes you specified in LanguageOptions.

    You can only use this parameter if you’ve included IdentifyLanguage and LanguageOptions in your request.

    
    
  • identify_multiple_languages(bool) / set_identify_multiple_languages(Option<bool>):
    required: false
    

    Enables automatic multi-language identification in your transcription job request. Use this parameter if your stream contains more than one language. If your stream contains only one language, use IdentifyLanguage instead.

    If you include IdentifyMultipleLanguages, you can optionally include a list of language codes, using LanguageOptions, that you think may be present in your stream. Including LanguageOptions restricts IdentifyMultipleLanguages to only the language options that you specify, which can improve transcription accuracy.

    If you want to apply a custom vocabulary or a custom vocabulary filter to your automatic multiple language identification request, include VocabularyNames or VocabularyFilterNames.

    Note that you must include one of LanguageCode, IdentifyLanguage, or IdentifyMultipleLanguages in your request. If you include more than one of these parameters, your transcription job fails.

    
    
  • vocabulary_names(impl Into<String>) / set_vocabulary_names(Option<String>):
    required: false
    

    Specify the names of the custom vocabularies that you want to use when processing your transcription. Note that vocabulary names are case sensitive.

    If none of the languages of the specified custom vocabularies match the language identified in your media, your job fails.

    This parameter is only intended for use with the IdentifyLanguage parameter. If you’re not including IdentifyLanguage in your request and want to use a custom vocabulary with your transcription, use the VocabularyName parameter instead.

    For more information, see Custom vocabularies.

    
    
  • vocabulary_filter_names(impl Into<String>) / set_vocabulary_filter_names(Option<String>):
    required: false
    

    Specify the names of the custom vocabulary filters that you want to use when processing your transcription. Note that vocabulary filter names are case sensitive.

    If none of the languages of the specified custom vocabulary filters match the language identified in your media, your job fails.

    This parameter is only intended for use with the IdentifyLanguage parameter. If you’re not including IdentifyLanguage in your request and want to use a custom vocabulary filter with your transcription, use the VocabularyFilterName parameter instead.

    For more information, see Using vocabulary filtering with unwanted words.

    
    
• On success, responds with StartStreamTranscriptionOutput with field(s):
  • request_id(Option<String>):

    Provides the identifier for your streaming request.

  • language_code(Option<LanguageCode>):

    Provides the language code that you specified in your request.

  • media_sample_rate_hertz(Option<i32>):

    Provides the sample rate that you specified in your request.

  • media_encoding(Option<MediaEncoding>):

    Provides the media encoding you specified in your request.

  • vocabulary_name(Option<String>):

    Provides the name of the custom vocabulary that you specified in your request.

  • session_id(Option<String>):

    Provides the identifier for your transcription session.

  • transcript_result_stream(EventReceiver<TranscriptResultStream, TranscriptResultStreamError>):

    Provides detailed information about your streaming session.

  • vocabulary_filter_name(Option<String>):

    Provides the name of the custom vocabulary filter that you specified in your request.

  • vocabulary_filter_method(Option<VocabularyFilterMethod>):

    Provides the vocabulary filtering method used in your transcription.

  • show_speaker_label(bool):

    Shows whether speaker partitioning was enabled for your transcription.

  • enable_channel_identification(bool):

    Shows whether channel identification was enabled for your transcription.

  • number_of_channels(Option<i32>):

    Provides the number of channels that you specified in your request.

  • enable_partial_results_stabilization(bool):

    Shows whether partial results stabilization was enabled for your transcription.

  • partial_results_stability(Option<PartialResultsStability>):

    Provides the stabilization level used for your transcription.

  • content_identification_type(Option<ContentIdentificationType>):

    Shows whether content identification was enabled for your transcription.

  • content_redaction_type(Option<ContentRedactionType>):

    Shows whether content redaction was enabled for your transcription.

  • pii_entity_types(Option<String>):

    Lists the PII entity types you specified in your request.

  • language_model_name(Option<String>):

    Provides the name of the custom language model that you specified in your request.

  • identify_language(bool):

    Shows whether automatic language identification was enabled for your transcription.

  • language_options(Option<String>):

    Provides the language codes that you specified in your request.

  • preferred_language(Option<LanguageCode>):

    Provides the preferred language that you specified in your request.

  • identify_multiple_languages(bool):

    Shows whether automatic multi-language identification was enabled for your transcription.

  • vocabulary_names(Option<String>):

    Provides the names of the custom vocabularies that you specified in your request.

  • vocabulary_filter_names(Option<String>):

    Provides the names of the custom vocabulary filters that you specified in your request.

• On failure, responds with SdkError<StartStreamTranscriptionError>

impl Client

pub fn from_conf(conf: Config) -> Self

Creates a new client from the service Config.

Panics

This method will panic in the following cases:

• Retries or timeouts are enabled without a sleep_impl configured.
• Identity caching is enabled without a sleep_impl and time_source configured.
• No behavior_version is provided.

The panic message for each of these will have instructions on how to resolve them.

pub fn config(&self) -> &Config

Returns the client’s configuration.

impl Client

pub fn new(sdk_config: &SdkConfig) -> Self

Creates a new client from an SDK Config.

Panics

• This method will panic if the sdk_config is missing an async sleep implementation. If you experience this panic, set the sleep_impl on the Config passed into this function to fix it.
• This method will panic if the sdk_config is missing an HTTP connector. If you experience this panic, set the http_connector on the Config passed into this function to fix it.
• This method will panic if no BehaviorVersion is provided. If you experience this panic, set behavior_version on the Config or enable the behavior-version-latest Cargo feature.

Trait Implementations

impl Clone for Client

fn clone(&self) -> Client

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Client

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.