Module Smaws_Client_Transcribe

Transcribe client library built on EIO.

Types

type vocabulary_state =
  1. | FAILED
  2. | READY
  3. | PENDING
type language_code =
  1. | ZU_ZA
  2. | WO_SN
  3. | UZ_UZ
  4. | UK_UA
  5. | UG_CN
  6. | TT_RU
  7. | TL_PH
  8. | SW_UG
  9. | SW_TZ
  10. | SW_RW
  11. | SW_KE
  12. | SW_BI
  13. | SU_ID
  14. | SR_RS
  15. | SO_SO
  16. | SL_SI
  17. | SK_SK
  18. | SI_LK
  19. | RW_RW
  20. | RO_RO
  21. | PS_AF
  22. | PL_PL
  23. | PA_IN
  24. | OR_IN
  25. | NO_NO
  26. | MT_MT
  27. | MR_IN
  28. | MN_MN
  29. | ML_IN
  30. | MK_MK
  31. | MI_NZ
  32. | MHR_RU
  33. | LV_LV
  34. | LT_LT
  35. | LG_IN
  36. | KY_KG
  37. | KN_IN
  38. | KK_KZ
  39. | KAB_DZ
  40. | KA_GE
  41. | IS_IS
  42. | HY_AM
  43. | HU_HU
  44. | HR_HR
  45. | HA_NG
  46. | GU_IN
  47. | GL_ES
  48. | FI_FI
  49. | EU_ES
  50. | ET_ET
  51. | EL_GR
  52. | CY_WL
  53. | CS_CZ
  54. | CKB_IR
  55. | CKB_IQ
  56. | CA_ES
  57. | BS_BA
  58. | BN_IN
  59. | BG_BG
  60. | BE_BY
  61. | BA_RU
  62. | AZ_AZ
  63. | AST_ES
  64. | AB_GE
  65. | SV_SE
  66. | VI_VN
  67. | EN_NZ
  68. | EN_ZA
  69. | TH_TH
  70. | ZH_TW
  71. | ZH_CN
  72. | TR_TR
  73. | TE_IN
  74. | TA_IN
  75. | RU_RU
  76. | PT_PT
  77. | PT_BR
  78. | NL_NL
  79. | MS_MY
  80. | KO_KR
  81. | JA_JP
  82. | IT_IT
  83. | ID_ID
  84. | HI_IN
  85. | HE_IL
  86. | FR_FR
  87. | FR_CA
  88. | FA_IR
  89. | ES_US
  90. | ES_ES
  91. | EN_WL
  92. | EN_US
  93. | EN_IN
  94. | EN_IE
  95. | EN_GB
  96. | EN_AU
  97. | EN_AB
  98. | DE_DE
  99. | DE_CH
  100. | DA_DK
  101. | AR_SA
  102. | AR_AE
  103. | AF_ZA
type vocabulary_info = {
  1. vocabulary_state : vocabulary_state option;
    (*

    The processing state of your custom vocabulary. If the state is READY, you can use the custom vocabulary in a StartTranscriptionJob request.

    *)
  2. last_modified_time : float option;
    (*

    The date and time the specified custom vocabulary was last modified.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents 12:32 PM UTC-7 on May 4, 2022.

    *)
  3. language_code : language_code option;
    (*

    The language code used to create your custom vocabulary. Each custom vocabulary must contain terms in only one language.

    A custom vocabulary can only be used to transcribe files in the same language as the custom vocabulary. For example, if you create a custom vocabulary using US English (en-US), you can only apply this custom vocabulary to files that contain English audio.

    *)
  4. vocabulary_name : string option;
    (*

    A unique name, chosen by you, for your custom vocabulary. This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account.

    *)
}

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

type vocabulary_filter_info = {
  1. last_modified_time : float option;
    (*

    The date and time the specified custom vocabulary filter was last modified.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents 12:32 PM UTC-7 on May 4, 2022.

    *)
  2. language_code : language_code option;
    (*

    The language code that represents the language of the entries in your vocabulary filter. Each custom vocabulary filter must contain terms in only one language.

    A custom vocabulary filter can only be used to transcribe files in the same language as the filter. For example, if you create a custom vocabulary filter using US English (en-US), you can only apply this filter to files that contain English audio.

    For a list of supported languages and their associated language codes, refer to the Supported languages table.

    *)
  3. vocabulary_filter_name : string option;
    (*

    A unique name, chosen by you, for your custom vocabulary filter. This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account.

    *)
}

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

type vocabulary_filter_method =
  1. | TAG
  2. | MASK
  3. | REMOVE
type update_vocabulary_response = {
  1. vocabulary_state : vocabulary_state option;
    (*

    The processing state of your custom vocabulary. If the state is READY, you can use the custom vocabulary in a StartTranscriptionJob request.

    *)
  2. last_modified_time : float option;
    (*

    The date and time the specified custom vocabulary was last updated.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents 12:32 PM UTC-7 on May 4, 2022.

    *)
  3. language_code : language_code option;
    (*

    The language code you selected for your custom vocabulary.

    *)
  4. vocabulary_name : string option;
    (*

    The name of the updated custom vocabulary.

    *)
}
type update_vocabulary_request = {
  1. data_access_role_arn : string option;
    (*

    The Amazon Resource Name (ARN) of an IAM role that has permissions to access the Amazon S3 bucket that contains your input files (in this case, your custom vocabulary). If the role that you specify doesn’t have the appropriate permissions to access the specified Amazon S3 location, your request fails.

    IAM role ARNs have the format arn:partition:iam::account:role/role-name-with-path. For example: arn:aws:iam::111122223333:role/Admin.

    For more information, see IAM ARNs.

    *)
  2. vocabulary_file_uri : string option;
    (*

    The Amazon S3 location of the text file that contains your custom vocabulary. The URI must be located in the same Amazon Web Services Region as the resource you're calling.

    Here's an example URI path: s3://DOC-EXAMPLE-BUCKET/my-vocab-file.txt

    Note that if you include VocabularyFileUri in your request, you cannot use the Phrases flag; you must choose one or the other.

    *)
  3. phrases : string list option;
    (*

    Use this parameter if you want to update your custom vocabulary by including all desired terms, as comma-separated values, within your request. The other option for updating your custom vocabulary is to save your entries in a text file and upload them to an Amazon S3 bucket, then specify the location of your file using the VocabularyFileUri parameter.

    Note that if you include Phrases in your request, you cannot use VocabularyFileUri; you must choose one or the other.

    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 to get the character set for your language.

    *)
  4. language_code : language_code;
    (*

    The language code that represents the language of the entries in the custom vocabulary you want to update. Each custom vocabulary must contain terms in only one language.

    A custom vocabulary can only be used to transcribe files in the same language as the custom vocabulary. For example, if you create a custom vocabulary using US English (en-US), you can only apply this custom vocabulary to files that contain English audio.

    For a list of supported languages and their associated language codes, refer to the Supported languages table.

    *)
  5. vocabulary_name : string;
    (*

    The name of the custom vocabulary you want to update. Custom vocabulary names are case sensitive.

    *)
}
type update_vocabulary_filter_response = {
  1. last_modified_time : float option;
    (*

    The date and time the specified custom vocabulary filter was last updated.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents 12:32 PM UTC-7 on May 4, 2022.

    *)
  2. language_code : language_code option;
    (*

    The language code you selected for your custom vocabulary filter.

    *)
  3. vocabulary_filter_name : string option;
    (*

    The name of the updated custom vocabulary filter.

    *)
}
type update_vocabulary_filter_request = {
  1. data_access_role_arn : string option;
    (*

    The Amazon Resource Name (ARN) of an IAM role that has permissions to access the Amazon S3 bucket that contains your input files (in this case, your custom vocabulary filter). If the role that you specify doesn’t have the appropriate permissions to access the specified Amazon S3 location, your request fails.

    IAM role ARNs have the format arn:partition:iam::account:role/role-name-with-path. For example: arn:aws:iam::111122223333:role/Admin.

    For more information, see IAM ARNs.

    *)
  2. vocabulary_filter_file_uri : string option;
    (*

    The Amazon S3 location of the text file that contains your custom vocabulary filter terms. The URI must be located in the same Amazon Web Services Region as the resource you're calling.

    Here's an example URI path: s3://DOC-EXAMPLE-BUCKET/my-vocab-filter-file.txt

    Note that if you include VocabularyFilterFileUri in your request, you cannot use Words; you must choose one or the other.

    *)
  3. words : string list option;
    (*

    Use this parameter if you want to update your custom vocabulary filter by including all desired terms, as comma-separated values, within your request. The other option for updating your vocabulary filter is to save your entries in a text file and upload them to an Amazon S3 bucket, then specify the location of your file using the VocabularyFilterFileUri parameter.

    Note that if you include Words in your request, you cannot use VocabularyFilterFileUri; you must choose one or the other.

    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 to get the character set for your language.

    *)
  4. vocabulary_filter_name : string;
    (*

    The name of the custom vocabulary filter you want to update. Custom vocabulary filter names are case sensitive.

    *)
}
type not_found_exception = {
  1. message : string option;
}

We can't find the requested resource. Check that the specified name is correct and try your request again.

type limit_exceeded_exception = {
  1. message : string option;
}

You've either sent too many requests or your input file is too long. Wait before retrying your request, or use a smaller file and try your request again.

type internal_failure_exception = {
  1. message : string option;
}

There was an internal error. Check the error message, correct the issue, and try your request again.

type bad_request_exception = {
  1. message : string option;
}

Your request didn't pass one or more validation tests. This can occur when the entity you're trying to delete doesn't exist or if it's in a non-terminal state (such as IN PROGRESS). See the exception message field for more information.

type conflict_exception = {
  1. message : string option;
}

A resource already exists with this name. Resource names must be unique within an Amazon Web Services account.

type update_medical_vocabulary_response = {
  1. vocabulary_state : vocabulary_state option;
    (*

    The processing state of your custom medical vocabulary. If the state is READY, you can use the custom vocabulary in a StartMedicalTranscriptionJob request.

    *)
  2. last_modified_time : float option;
    (*

    The date and time the specified custom medical vocabulary was last updated.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents 12:32 PM UTC-7 on May 4, 2022.

    *)
  3. language_code : language_code option;
    (*

    The language code you selected for your custom medical vocabulary. US English (en-US) is the only language supported with Amazon Transcribe Medical.

    *)
  4. vocabulary_name : string option;
    (*

    The name of the updated custom medical vocabulary.

    *)
}
type update_medical_vocabulary_request = {
  1. vocabulary_file_uri : string;
    (*

    The Amazon S3 location of the text file that contains your custom medical vocabulary. The URI must be located in the same Amazon Web Services Region as the resource you're calling.

    Here's an example URI path: s3://DOC-EXAMPLE-BUCKET/my-vocab-file.txt

    *)
  2. language_code : language_code;
    (*

    The language code that represents the language of the entries in the custom vocabulary you want to update. US English (en-US) is the only language supported with Amazon Transcribe Medical.

    *)
  3. vocabulary_name : string;
    (*

    The name of the custom medical vocabulary you want to update. Custom medical vocabulary names are case sensitive.

    *)
}
type absolute_time_range = {
  1. last : int option;
    (*

    The time, in milliseconds, from the specified value until the end of your media file. Amazon Transcribe searches for your specified criteria in this time segment.

    *)
  2. first : int option;
    (*

    The time, in milliseconds, from the start of your media file until the specified value. Amazon Transcribe searches for your specified criteria in this time segment.

    *)
  3. end_time : int option;
    (*

    The time, in milliseconds, when Amazon Transcribe stops searching for the specified criteria in your audio. If you include EndTime in your request, you must also include StartTime.

    *)
  4. start_time : int option;
    (*

    The time, in milliseconds, when Amazon Transcribe starts searching for the specified criteria in your audio. If you include StartTime in your request, you must also include EndTime.

    *)
}

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 .

type relative_time_range = {
  1. last : int option;
    (*

    The time, in percentage, from the specified value until the end of your media file. Amazon Transcribe searches for your specified criteria in this time segment.

    *)
  2. first : int option;
    (*

    The time, in percentage, from the start of your media file until the specified value. Amazon Transcribe searches for your specified criteria in this time segment.

    *)
  3. end_percentage : int option;
    (*

    The time, in percentage, when Amazon Transcribe stops searching for the specified criteria in your media file. If you include EndPercentage in your request, you must also include StartPercentage.

    *)
  4. start_percentage : int option;
    (*

    The time, in percentage, when Amazon Transcribe starts searching for the specified criteria in your media file. If you include StartPercentage in your request, you must also include EndPercentage.

    *)
}

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 .

type non_talk_time_filter = {
  1. negate : bool option;
    (*

    Set to TRUE to flag periods of speech. Set to FALSE to flag periods of silence

    *)
  2. relative_time_range : relative_time_range option;
    (*

    Makes it possible to specify a time range (in percentage) in your media file, during which you want to search for a period of silence. See for more detail.

    *)
  3. absolute_time_range : absolute_time_range option;
    (*

    Makes it possible to specify a time range (in milliseconds) in your audio, during which you want to search for a period of silence. See for more detail.

    *)
  4. threshold : int option;
    (*

    Specify the duration, in milliseconds, of the period of silence that you want to flag. For example, you can flag a silent period that lasts 30,000 milliseconds.

    *)
}

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.

type participant_role =
  1. | CUSTOMER
  2. | AGENT
type interruption_filter = {
  1. negate : bool option;
    (*

    Set to TRUE to flag speech that does not contain interruptions. Set to FALSE to flag speech that contains interruptions.

    *)
  2. relative_time_range : relative_time_range option;
    (*

    Makes it possible to specify a time range (in percentage) in your media file, during which you want to search for an interruption. See for more detail.

    *)
  3. absolute_time_range : absolute_time_range option;
    (*

    Makes it possible to specify a time range (in milliseconds) in your audio, during which you want to search for an interruption. See for more detail.

    *)
  4. participant_role : participant_role option;
    (*

    Specify the interrupter that you want to flag. Omitting this parameter is equivalent to specifying both participants.

    *)
  5. threshold : int option;
    (*

    Specify the duration of the interruptions in milliseconds. For example, you can flag speech that contains more than 10,000 milliseconds of interruptions.

    *)
}

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.

type transcript_filter_type =
  1. | EXACT
type transcript_filter = {
  1. targets : string list;
    (*

    Specify the phrases that you want to flag.

    *)
  2. negate : bool option;
    (*

    Set to TRUE to flag the absence of the phrase that you specified in your request. Set to FALSE to flag the presence of the phrase that you specified in your request.

    *)
  3. participant_role : participant_role option;
    (*

    Specify the participant that you want to flag. Omitting this parameter is equivalent to specifying both participants.

    *)
  4. relative_time_range : relative_time_range option;
    (*

    Makes it possible to specify a time range (in percentage) in your media file, during which you want to search for the specified key words or phrases. See for more detail.

    *)
  5. absolute_time_range : absolute_time_range option;
    (*

    Makes it possible to specify a time range (in milliseconds) in your audio, during which you want to search for the specified key words or phrases. See for more detail.

    *)
  6. transcript_filter_type : transcript_filter_type;
    (*

    Flag the presence or absence of an exact match to the phrases that you specify. For example, if you specify the phrase "speak to a manager" as your Targets value, only that exact phrase is flagged.

    Note that semantic matching is not supported. For example, if your customer says "speak to the manager", instead of "speak to a manager", your content is not flagged.

    *)
}

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.

type sentiment_value =
  1. | MIXED
  2. | NEUTRAL
  3. | NEGATIVE
  4. | POSITIVE
type sentiment_filter = {
  1. negate : bool option;
    (*

    Set to TRUE to flag the sentiments that you didn't include in your request. Set to FALSE to flag the sentiments that you specified in your request.

    *)
  2. participant_role : participant_role option;
    (*

    Specify the participant that you want to flag. Omitting this parameter is equivalent to specifying both participants.

    *)
  3. relative_time_range : relative_time_range option;
    (*

    Makes it possible to specify a time range (in percentage) in your media file, during which you want to search for the specified sentiments. See for more detail.

    *)
  4. absolute_time_range : absolute_time_range option;
    (*

    Makes it possible to specify a time range (in milliseconds) in your audio, during which you want to search for the specified sentiments. See for more detail.

    *)
  5. sentiments : sentiment_value list;
    (*

    Specify the sentiments that you want to flag.

    *)
}

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.

type rule =
  1. | SentimentFilter of sentiment_filter
  2. | TranscriptFilter of transcript_filter
  3. | InterruptionFilter of interruption_filter
  4. | NonTalkTimeFilter of non_talk_time_filter

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.

type input_type =
  1. | POST_CALL
  2. | REAL_TIME
type category_properties = {
  1. input_type : input_type option;
    (*

    The input type associated with the specified category. POST_CALL refers to a category that is applied to batch transcriptions; REAL_TIME refers to a category that is applied to streaming transcriptions.

    *)
  2. last_update_time : float option;
    (*

    The date and time the specified Call Analytics category was last updated.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-05T12:45:32.691000-07:00 represents 12:45 PM UTC-7 on May 5, 2022.

    *)
  3. create_time : float option;
    (*

    The date and time the specified Call Analytics category was created.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents 12:32 PM UTC-7 on May 4, 2022.

    *)
  4. rules : rule list option;
    (*

    The rules used to define a Call Analytics category. Each category can have between 1 and 20 rules.

    *)
  5. category_name : string option;
    (*

    The name of the Call Analytics category. Category names are case sensitive and must be unique within an Amazon Web Services account.

    *)
}

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.

type update_call_analytics_category_response = {
  1. category_properties : category_properties option;
    (*

    Provides you with the properties of the Call Analytics category you specified in your UpdateCallAnalyticsCategory request.

    *)
}
type update_call_analytics_category_request = {
  1. input_type : input_type option;
    (*

    Choose whether you want to update a real-time or a post-call category. The input type you specify must match the input type specified when the category was created. For example, if you created a category with the POST_CALL input type, you must use POST_CALL as the input type when updating this category.

    *)
  2. rules : rule list;
    (*

    The rules used for the updated Call Analytics category. The rules you provide in this field replace the ones that are currently being used in the specified category.

    *)
  3. category_name : string;
    (*

    The name of the Call Analytics category you want to update. Category names are case sensitive.

    *)
}
type untag_resource_response = unit
type untag_resource_request = {
  1. tag_keys : string list;
    (*

    Removes the specified tag keys from the specified Amazon Transcribe resource.

    *)
  2. resource_arn : string;
    (*

    The Amazon Resource Name (ARN) of the Amazon Transcribe resource you want to remove tags from. ARNs have the format arn:partition:service:region:account-id:resource-type/resource-id.

    For example, arn:aws:transcribe:us-west-2:111122223333:transcription-job/transcription-job-name.

    Valid values for resource-type are: transcription-job, medical-transcription-job, vocabulary, medical-vocabulary, vocabulary-filter, and language-model.

    *)
}
type type_ =
  1. | DICTATION
  2. | CONVERSATION
type transcription_job_status =
  1. | COMPLETED
  2. | FAILED
  3. | IN_PROGRESS
  4. | QUEUED
type output_location_type =
  1. | SERVICE_BUCKET
  2. | CUSTOMER_BUCKET
type redaction_type =
  1. | PII
type redaction_output =
  1. | REDACTED_AND_UNREDACTED
  2. | REDACTED
type pii_entity_type =
  1. | ALL
  2. | SSN
  3. | PHONE
  4. | NAME
  5. | ADDRESS
  6. | EMAIL
  7. | PIN
  8. | CREDIT_DEBIT_EXPIRY
  9. | CREDIT_DEBIT_CVV
  10. | CREDIT_DEBIT_NUMBER
  11. | BANK_ROUTING
  12. | BANK_ACCOUNT_NUMBER
type content_redaction = {
  1. pii_entity_types : pii_entity_type list option;
    (*

    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. If you do not include PiiEntityTypes in your request, all PII is redacted.

    *)
  2. redaction_output : redaction_output;
    (*

    Specify if you want only a redacted transcript, or if you want a redacted and an unredacted transcript.

    When you choose redacted Amazon Transcribe creates only a redacted transcript.

    When you choose redacted_and_unredacted Amazon Transcribe creates a redacted and an unredacted transcript (as two separate files).

    *)
  3. redaction_type : redaction_type;
    (*

    Specify the category of information you want to redact; PII (personally identifiable information) is the only valid value. You can use PiiEntityTypes to choose which types of PII you want to redact. If you do not include PiiEntityTypes in your request, all PII is redacted.

    *)
}

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.

type model_settings = {
  1. language_model_name : string option;
    (*

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

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

    *)
}

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.

type language_code_item = {
  1. duration_in_seconds : float option;
    (*

    Provides the total time, in seconds, each identified language is spoken in your media.

    *)
  2. language_code : language_code option;
    (*

    Provides the language code for each language identified in your media.

    *)
}

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.

type toxicity_category =
  1. | ALL
type toxicity_detection_settings = {
  1. toxicity_categories : toxicity_category list;
    (*

    If you include ToxicityDetection in your transcription request, you must also include ToxicityCategories. The only accepted value for this parameter is ALL.

    *)
}

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

type transcription_job_summary = {
  1. toxicity_detection : toxicity_detection_settings list option;
    (*

    Indicates whether toxicity detection was enabled for the specified transcription job.

    *)
  2. language_codes : language_code_item list option;
    (*

    The language codes used to create your transcription job. This parameter is used with multi-language identification. For single-language identification, the singular version of this parameter, LanguageCode, is present.

    *)
  3. identified_language_score : float option;
    (*

    The confidence score associated with the language identified in your media file.

    Confidence scores are values between 0 and 1; a larger value indicates a higher probability that the identified language correctly matches the language spoken in your media.

    *)
  4. identify_multiple_languages : bool option;
    (*

    Indicates whether automatic multi-language identification was enabled (TRUE) for the specified transcription job.

    *)
  5. identify_language : bool option;
    (*

    Indicates whether automatic language identification was enabled (TRUE) for the specified transcription job.

    *)
  6. model_settings : model_settings option;
  7. content_redaction : content_redaction option;
    (*

    The content redaction settings of the transcription job.

    *)
  8. output_location_type : output_location_type option;
    (*

    Indicates where the specified transcription output is stored.

    If the value is CUSTOMER_BUCKET, the location is the Amazon S3 bucket you specified using the OutputBucketName parameter in your request. If you also included OutputKey in your request, your output is located in the path you specified in your request.

    If the value is SERVICE_BUCKET, the location is a service-managed Amazon S3 bucket. To access a transcript stored in a service-managed bucket, use the URI shown in the TranscriptFileUri or RedactedTranscriptFileUri field.

    *)
  9. failure_reason : string option;
    (*

    If TranscriptionJobStatus is FAILED, FailureReason contains information about why the transcription job failed. See also: Common Errors.

    *)
  10. transcription_job_status : transcription_job_status option;
    (*

    Provides the status of your transcription job.

    If the status is COMPLETED, the job is finished and you can find the results at the location specified in TranscriptFileUri (or RedactedTranscriptFileUri, if you requested transcript redaction). If the status is FAILED, FailureReason provides details on why your transcription job failed.

    *)
  11. language_code : language_code option;
    (*

    The language code used to create your transcription.

    *)
  12. completion_time : float option;
    (*

    The date and time the specified transcription job finished processing.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:33:13.922000-07:00 represents a transcription job that started processing at 12:33 PM UTC-7 on May 4, 2022.

    *)
  13. start_time : float option;
    (*

    The date and time your transcription job began processing.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.789000-07:00 represents a transcription job that started processing at 12:32 PM UTC-7 on May 4, 2022.

    *)
  14. creation_time : float option;
    (*

    The date and time the specified transcription job request was made.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents a transcription job that started processing at 12:32 PM UTC-7 on May 4, 2022.

    *)
  15. transcription_job_name : string option;
    (*

    The name of the transcription job. Job names are case sensitive and must be unique within an Amazon Web Services account.

    *)
}

Provides detailed information about a specific transcription job.

type media_format =
  1. | M4A
  2. | WEBM
  3. | AMR
  4. | OGG
  5. | FLAC
  6. | WAV
  7. | MP4
  8. | MP3
type media = {
  1. redacted_media_file_uri : string option;
    (*

    The Amazon S3 location of the media file you want to redact. For example:

    • s3://DOC-EXAMPLE-BUCKET/my-media-file.flac
    • s3://DOC-EXAMPLE-BUCKET/media-files/my-media-file.flac

    Note that the Amazon S3 bucket that contains your input media must be located in the same Amazon Web Services Region where you're making your transcription request.

    RedactedMediaFileUri produces a redacted audio file in addition to a redacted transcript. It is only supported for Call Analytics (StartCallAnalyticsJob) transcription requests.

    *)
  2. media_file_uri : string option;
    (*

    The Amazon S3 location of the media file you want to transcribe. For example:

    • s3://DOC-EXAMPLE-BUCKET/my-media-file.flac
    • s3://DOC-EXAMPLE-BUCKET/media-files/my-media-file.flac

    Note that the Amazon S3 bucket that contains your input media must be located in the same Amazon Web Services Region where you're making your transcription request.

    *)
}

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.

type transcript = {
  1. redacted_transcript_file_uri : string option;
    (*

    The Amazon S3 location of your redacted transcript. You can use this URI to access or download your transcript.

    If you included OutputBucketName in your transcription job request, this is the URI of that bucket. If you also included OutputKey in your request, your output is located in the path you specified in your request.

    If you didn't include OutputBucketName in your transcription job request, your transcript is stored in a service-managed bucket, and RedactedTranscriptFileUri provides you with a temporary URI you can use for secure access to your transcript.

    Temporary URIs for service-managed Amazon S3 buckets are only valid for 15 minutes. If you get an AccesDenied error, you can get a new temporary URI by running a GetTranscriptionJob or ListTranscriptionJob request.

    *)
  2. transcript_file_uri : string option;
    (*

    The Amazon S3 location of your transcript. You can use this URI to access or download your transcript.

    If you included OutputBucketName in your transcription job request, this is the URI of that bucket. If you also included OutputKey in your request, your output is located in the path you specified in your request.

    If you didn't include OutputBucketName in your transcription job request, your transcript is stored in a service-managed bucket, and TranscriptFileUri provides you with a temporary URI you can use for secure access to your transcript.

    Temporary URIs for service-managed Amazon S3 buckets are only valid for 15 minutes. If you get an AccesDenied error, you can get a new temporary URI by running a GetTranscriptionJob or ListTranscriptionJob request.

    *)
}

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

type settings = {
  1. vocabulary_filter_method : vocabulary_filter_method option;
    (*

    Specify how you want your custom 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.

    *)
  2. vocabulary_filter_name : string option;
    (*

    The name of the custom vocabulary filter you want to use in your transcription job request. This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account.

    Note that if you include VocabularyFilterName in your request, you must also include VocabularyFilterMethod.

    *)
  3. max_alternatives : int option;
    (*

    Indicate the maximum number of alternative transcriptions you want Amazon Transcribe to include in your transcript.

    If you select a number greater than the number of alternative transcriptions generated by Amazon Transcribe, only the actual number of alternative transcriptions are included.

    If you include MaxAlternatives in your request, you must also include ShowAlternatives with a value of true.

    For more information, see Alternative transcriptions.

    *)
  4. show_alternatives : bool option;
    (*

    To include alternative transcriptions within your transcription output, include ShowAlternatives in your transcription request.

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

    If you include ShowAlternatives, you must also include MaxAlternatives, which is the maximum number of alternative transcriptions you want Amazon Transcribe to generate.

    For more information, see Alternative transcriptions.

    *)
  5. channel_identification : bool option;
    (*

    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.

    For more information, see Transcribing multi-channel audio.

    *)
  6. max_speaker_labels : int option;
    (*

    Specify the maximum number of speakers you want to partition in your media.

    Note that if your media contains more speakers than the specified number, multiple speakers are treated as a single speaker.

    If you specify the MaxSpeakerLabels field, you must set the ShowSpeakerLabels field to true.

    *)
  7. show_speaker_labels : bool option;
    (*

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

    If you enable ShowSpeakerLabels in your request, you must also include MaxSpeakerLabels.

    For more information, see Partitioning speakers (diarization).

    *)
  8. vocabulary_name : string option;
    (*

    The name of the custom vocabulary you want to use in your transcription job request. This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account.

    *)
}

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.

type job_execution_settings = {
  1. data_access_role_arn : string option;
    (*

    The Amazon Resource Name (ARN) of an IAM role that has permissions to access the Amazon S3 bucket that contains your input files. If the role that you specify doesn’t have the appropriate permissions to access the specified Amazon S3 location, your request fails.

    IAM role ARNs have the format arn:partition:iam::account:role/role-name-with-path. For example: arn:aws:iam::111122223333:role/Admin. For more information, see IAM ARNs.

    Note that if you include DataAccessRoleArn in your request, you must also include AllowDeferredExecution.

    *)
  2. allow_deferred_execution : bool option;
    (*

    Makes it possible to enable job queuing when your concurrent request limit is exceeded. When AllowDeferredExecution is set to true, transcription job requests are placed in a queue until the number of jobs falls below the concurrent request limit. If AllowDeferredExecution is set to false and the number of transcription job requests exceed the concurrent request limit, you get a LimitExceededException error.

    If you include AllowDeferredExecution in your request, you must also include DataAccessRoleArn.

    *)
}

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.

type tag = {
  1. value : string;
    (*

    The second part of a key:value pair that forms a tag associated with a given resource. For example, in the tag Department:Sales, the value is 'Sales'.

    Note that you can set the value of a tag to an empty string, but you can't set the value of a tag to null. Omitting the tag value is the same as using an empty string.

    *)
  2. key : string;
    (*

    The first part of a key:value pair that forms a tag associated with a given resource. For example, in the tag Department:Sales, the key is 'Department'.

    *)
}

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.

type subtitle_format =
  1. | SRT
  2. | VTT
type subtitles_output = {
  1. output_start_index : int option;
    (*

    Provides the start index value for your subtitle files. If you did not specify a value in your request, the default value of 0 is used.

    *)
  2. subtitle_file_uris : string list option;
    (*

    The Amazon S3 location of your transcript. You can use this URI to access or download your subtitle file. Your subtitle file is stored in the same location as your transcript. If you specified both WebVTT and SubRip subtitle formats, two URIs are provided.

    If you included OutputBucketName in your transcription job request, this is the URI of that bucket. If you also included OutputKey in your request, your output is located in the path you specified in your request.

    If you didn't include OutputBucketName in your transcription job request, your subtitle file is stored in a service-managed bucket, and TranscriptFileUri provides you with a temporary URI you can use for secure access to your subtitle file.

    Temporary URIs for service-managed Amazon S3 buckets are only valid for 15 minutes. If you get an AccesDenied error, you can get a new temporary URI by running a GetTranscriptionJob or ListTranscriptionJob request.

    *)
  3. formats : subtitle_format list option;
    (*

    Provides the format of your subtitle files. If your request included both WebVTT (vtt) and SubRip (srt) formats, both formats are shown.

    *)
}

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

type language_id_settings = {
  1. language_model_name : string option;
    (*

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

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

    *)
  2. vocabulary_filter_name : string option;
    (*

    The name of the custom vocabulary filter you want to use when processing your transcription job. Custom vocabulary filter names are case sensitive.

    The language of the specified custom vocabulary filter must match the language code that you specify in your transcription request. If the languages do not match, the custom vocabulary filter isn't applied. There are no errors or warnings associated with a language mismatch.

    Note that if you include VocabularyFilterName in your request, you must also include VocabularyFilterMethod.

    *)
  3. vocabulary_name : string option;
    (*

    The name of the custom vocabulary you want to use when processing your transcription job. Custom vocabulary names are case sensitive.

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

    *)
}

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.

type transcription_job = {
  1. toxicity_detection : toxicity_detection_settings list option;
    (*

    Provides information about the toxicity detection settings applied to your transcription.

    *)
  2. language_id_settings : (string * language_id_settings) list option;
    (*

    Provides the name and language of all custom language models, custom vocabularies, and custom vocabulary filters that you included in your request.

    *)
  3. subtitles : subtitles_output option;
    (*

    Indicates whether subtitles were generated with your transcription.

    *)
  4. tags : tag list option;
    (*

    The tags, each in the form of a key:value pair, assigned to the specified transcription job.

    *)
  5. language_codes : language_code_item list option;
    (*

    The language codes used to create your transcription job. This parameter is used with multi-language identification. For single-language identification requests, refer to the singular version of this parameter, LanguageCode.

    *)
  6. identified_language_score : float option;
    (*

    The confidence score associated with the language identified in your media file.

    Confidence scores are values between 0 and 1; a larger value indicates a higher probability that the identified language correctly matches the language spoken in your media.

    *)
  7. language_options : language_code list option;
    (*

    Provides the language codes you specified in your request.

    *)
  8. identify_multiple_languages : bool option;
    (*

    Indicates whether automatic multi-language identification was enabled (TRUE) for the specified transcription job.

    *)
  9. identify_language : bool option;
    (*

    Indicates whether automatic language identification was enabled (TRUE) for the specified transcription job.

    *)
  10. content_redaction : content_redaction option;
    (*

    Indicates whether redaction was enabled in your transcript.

    *)
  11. job_execution_settings : job_execution_settings option;
    (*

    Provides information about how your transcription job was processed. This parameter shows if your request was queued and what data access role was used.

    *)
  12. model_settings : model_settings option;
    (*

    Provides information on the custom language model you included in your request.

    *)
  13. settings : settings option;
    (*

    Provides information on any additional settings that were included in your request. Additional settings include channel identification, alternative transcriptions, speaker partitioning, custom vocabularies, and custom vocabulary filters.

    *)
  14. failure_reason : string option;
    (*

    If TranscriptionJobStatus is FAILED, FailureReason contains information about why the transcription job request failed.

    The FailureReason field contains one of the following values:

    • Unsupported media format.

      The media format specified in MediaFormat isn't valid. Refer to refer to the MediaFormat parameter for a list of supported formats.

    • The media format provided does not match the detected media format.

      The media format specified in MediaFormat doesn't match the format of the input file. Check the media format of your media file and correct the specified value.

    • Invalid sample rate for audio file.

      The sample rate specified in MediaSampleRateHertz isn't valid. The sample rate must be between 8,000 and 48,000 hertz.

    • The sample rate provided does not match the detected sample rate.

      The sample rate specified in MediaSampleRateHertz doesn't match the sample rate detected in your input media file. Check the sample rate of your media file and correct the specified value.

    • Invalid file size: file size too large.

      The size of your media file is larger than what Amazon Transcribe can process. For more information, refer to Service quotas.

    • Invalid number of channels: number of channels too large.

      Your audio contains more channels than Amazon Transcribe is able to process. For more information, refer to Service quotas.

    *)
  15. completion_time : float option;
    (*

    The date and time the specified transcription job finished processing.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:33:13.922000-07:00 represents a transcription job that started processing at 12:33 PM UTC-7 on May 4, 2022.

    *)
  16. creation_time : float option;
    (*

    The date and time the specified transcription job request was made.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents a transcription job that started processing at 12:32 PM UTC-7 on May 4, 2022.

    *)
  17. start_time : float option;
    (*

    The date and time the specified transcription job began processing.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.789000-07:00 represents a transcription job that started processing at 12:32 PM UTC-7 on May 4, 2022.

    *)
  18. transcript : transcript option;
    (*

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

    *)
  19. media : media option;
    (*

    Provides the Amazon S3 location of the media file you used in your request.

    *)
  20. media_format : media_format option;
    (*

    The format of the input media file.

    *)
  21. media_sample_rate_hertz : int option;
    (*

    The sample rate, in hertz, of the audio track in your input media file.

    *)
  22. language_code : language_code option;
    (*

    The language code used to create your transcription job. This parameter is used with single-language identification. For multi-language identification requests, refer to the plural version of this parameter, LanguageCodes.

    *)
  23. transcription_job_status : transcription_job_status option;
    (*

    Provides the status of the specified transcription job.

    If the status is COMPLETED, the job is finished and you can find the results at the location specified in TranscriptFileUri (or RedactedTranscriptFileUri, if you requested transcript redaction). If the status is FAILED, FailureReason provides details on why your transcription job failed.

    *)
  24. transcription_job_name : string option;
    (*

    The name of the transcription job. Job names are case sensitive and must be unique within an Amazon Web Services account.

    *)
}

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.

type tag_resource_response = unit
type tag_resource_request = {
  1. tags : tag list;
    (*

    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.

    *)
  2. resource_arn : string;
    (*

    The Amazon Resource Name (ARN) of the resource you want to tag. ARNs have the format arn:partition:service:region:account-id:resource-type/resource-id.

    For example, arn:aws:transcribe:us-west-2:111122223333:transcription-job/transcription-job-name.

    Valid values for resource-type are: transcription-job, medical-transcription-job, vocabulary, medical-vocabulary, vocabulary-filter, and language-model.

    *)
}
type start_transcription_job_response = {
  1. transcription_job : transcription_job option;
    (*

    Provides detailed information about the current transcription job, including job status and, if applicable, failure reason.

    *)
}
type subtitles = {
  1. output_start_index : int option;
    (*

    Specify the starting value that is assigned to the first subtitle segment.

    The default start index for Amazon Transcribe is 0, which differs from the more widely used standard of 1. If you're uncertain which value to use, we recommend choosing 1, as this may improve compatibility with other services.

    *)
  2. formats : subtitle_format list option;
    (*

    Specify the output format for your subtitle file; if you select both WebVTT (vtt) and SubRip (srt) formats, two output files are generated.

    *)
}

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.

type start_transcription_job_request = {
  1. toxicity_detection : toxicity_detection_settings list option;
    (*

    Enables toxic speech detection in your transcript. If you include ToxicityDetection in your request, you must also include ToxicityCategories.

    For information on the types of toxic speech Amazon Transcribe can detect, see Detecting toxic speech.

    *)
  2. language_id_settings : (string * language_id_settings) list option;
    (*

    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.

    *)
  3. tags : tag list option;
    (*

    Adds one or more custom tags, each in the form of a key:value pair, to a new transcription job at the time you start this new job.

    To learn more about using tags with Amazon Transcribe, refer to Tagging resources.

    *)
  4. subtitles : subtitles option;
    (*

    Produces subtitle files for your input media. You can specify WebVTT (*.vtt) and SubRip (*.srt) formats.

    *)
  5. language_options : language_code list option;
    (*

    You can 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.

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

    For more information, refer to Supported languages.

    To transcribe speech in Modern Standard Arabic (ar-SA), your media file must be encoded at a sample rate of 16,000 Hz or higher.

    *)
  6. identify_multiple_languages : bool option;
    (*

    Enables automatic multi-language identification in your transcription job request. Use this parameter if your media file contains more than one language. If your media 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 media file. Including LanguageOptions restricts IdentifyLanguage 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 language identification request, include LanguageIdSettings with the relevant sub-parameters (VocabularyName and VocabularyFilterName). If you include LanguageIdSettings, also include LanguageOptions.

    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.

    *)
  7. identify_language : bool option;
    (*

    Enables automatic language identification in your transcription job request. Use this parameter if your media file contains only one language. If your media contains multiple languages, use IdentifyMultipleLanguages instead.

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

    If you want to apply a custom language model, a custom vocabulary, or a custom vocabulary filter to your automatic language identification request, include LanguageIdSettings with the relevant sub-parameters (VocabularyName, LanguageModelName, and VocabularyFilterName). If you include LanguageIdSettings, also include LanguageOptions.

    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.

    *)
  8. content_redaction : content_redaction option;
    (*

    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. If you do not include PiiEntityTypes in your request, all PII is redacted.

    *)
  9. job_execution_settings : job_execution_settings option;
    (*

    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.

    *)
  10. model_settings : model_settings option;
    (*

    Specify the custom language model you want to include with your transcription job. If you include ModelSettings in your request, you must include the LanguageModelName sub-parameter.

    For more information, see Custom language models.

    *)
  11. settings : settings option;
    (*

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

    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 Settings with the VocabularyName or VocabularyFilterName (or both) sub-parameter.

    If you're using automatic language identification with your request and want to include a custom language model, a custom vocabulary, or a custom vocabulary filter, use instead the parameter with the LanguageModelName, VocabularyName or VocabularyFilterName sub-parameters.

    *)
  12. kms_encryption_context : (string * string) list option;
    (*

    A map of plain text, non-secret key:value pairs, known as encryption context pairs, that provide an added layer of security for your data. For more information, see KMS encryption context and Asymmetric keys in KMS.

    *)
  13. output_encryption_kms_key_id : string option;
    (*

    The KMS key you want to use to encrypt your transcription output.

    If using a key located in the current Amazon Web Services account, you can specify your KMS key in one of four ways:

    1. Use the KMS key ID itself. For example, 1234abcd-12ab-34cd-56ef-1234567890ab.
    2. Use an alias for the KMS key ID. For example, alias/ExampleAlias.
    3. Use the Amazon Resource Name (ARN) for the KMS key ID. For example, arn:aws:kms:region:account-ID:key/1234abcd-12ab-34cd-56ef-1234567890ab.
    4. Use the ARN for the KMS key alias. For example, arn:aws:kms:region:account-ID:alias/ExampleAlias.

    If using a key located in a different Amazon Web Services account than the current Amazon Web Services account, you can specify your KMS key in one of two ways:

    1. Use the ARN for the KMS key ID. For example, arn:aws:kms:region:account-ID:key/1234abcd-12ab-34cd-56ef-1234567890ab.
    2. Use the ARN for the KMS key alias. For example, arn:aws:kms:region:account-ID:alias/ExampleAlias.

    If you do not specify an encryption key, your output is encrypted with the default Amazon S3 key (SSE-S3).

    If you specify a KMS key to encrypt your output, you must also specify an output location using the OutputLocation parameter.

    Note that the role making the request must have permission to use the specified KMS key.

    *)
  14. output_key : string option;
    (*

    Use in combination with OutputBucketName to specify the output location of your transcript and, optionally, a unique name for your output file. The default name for your transcription output is the same as the name you specified for your transcription job (TranscriptionJobName).

    Here are some examples of how you can use OutputKey:

    • If you specify 'DOC-EXAMPLE-BUCKET' as the OutputBucketName and 'my-transcript.json' as the OutputKey, your transcription output path is s3://DOC-EXAMPLE-BUCKET/my-transcript.json.
    • If you specify 'my-first-transcription' as the TranscriptionJobName, 'DOC-EXAMPLE-BUCKET' as the OutputBucketName, and 'my-transcript' as the OutputKey, your transcription output path is s3://DOC-EXAMPLE-BUCKET/my-transcript/my-first-transcription.json.
    • If you specify 'DOC-EXAMPLE-BUCKET' as the OutputBucketName and 'test-files/my-transcript.json' as the OutputKey, your transcription output path is s3://DOC-EXAMPLE-BUCKET/test-files/my-transcript.json.
    • If you specify 'my-first-transcription' as the TranscriptionJobName, 'DOC-EXAMPLE-BUCKET' as the OutputBucketName, and 'test-files/my-transcript' as the OutputKey, your transcription output path is s3://DOC-EXAMPLE-BUCKET/test-files/my-transcript/my-first-transcription.json.

    If you specify the name of an Amazon S3 bucket sub-folder that doesn't exist, one is created for you.

    *)
  15. output_bucket_name : string option;
    (*

    The name of the Amazon S3 bucket where you want your transcription output stored. Do not include the S3:// prefix of the specified bucket.

    If you want your output to go to a sub-folder of this bucket, specify it using the OutputKey parameter; OutputBucketName only accepts the name of a bucket.

    For example, if you want your output stored in S3://DOC-EXAMPLE-BUCKET, set OutputBucketName to DOC-EXAMPLE-BUCKET. However, if you want your output stored in S3://DOC-EXAMPLE-BUCKET/test-files/, set OutputBucketName to DOC-EXAMPLE-BUCKET and OutputKey to test-files/.

    Note that Amazon Transcribe must have permission to use the specified location. You can change Amazon S3 permissions using the Amazon Web Services Management Console. See also Permissions Required for IAM User Roles.

    If you do not specify OutputBucketName, your transcript is placed in a service-managed Amazon S3 bucket and you are provided with a URI to access your transcript.

    *)
  16. media : media;
    (*

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

    *)
  17. media_format : media_format option;
    (*

    Specify the format of your input media file.

    *)
  18. media_sample_rate_hertz : int option;
    (*

    The sample rate, in hertz, of the audio track in your input media file.

    If you do not specify the media sample rate, Amazon Transcribe determines it for you. If you specify the sample rate, it must match the rate detected by Amazon Transcribe. If there's a mismatch between the value that you specify and the value detected, your job fails. In most cases, you can omit MediaSampleRateHertz and let Amazon Transcribe determine the sample rate.

    *)
  19. language_code : language_code option;
    (*

    The language code that represents the language spoken in the input media file.

    If you're unsure of the language spoken in your media file, consider using IdentifyLanguage or IdentifyMultipleLanguages to enable automatic language identification.

    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.

    For a list of supported languages and their associated language codes, refer to the Supported languages table.

    To transcribe speech in Modern Standard Arabic (ar-SA), your media file must be encoded at a sample rate of 16,000 Hz or higher.

    *)
  20. transcription_job_name : string;
    (*

    A unique name, chosen by you, for your transcription job. The name that you specify is also used as the default name of your transcription output file. If you want to specify a different name for your transcription output, use the OutputKey parameter.

    This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account. If you try to create a new job with the same name as an existing job, you get a ConflictException error.

    *)
}
type medical_transcript = {
  1. transcript_file_uri : string option;
    (*

    The Amazon S3 location of your transcript. You can use this URI to access or download your transcript.

    Note that this is the Amazon S3 location you specified in your request using the OutputBucketName parameter.

    *)
}

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

type medical_transcription_setting = {
  1. vocabulary_name : string option;
    (*

    The name of the custom vocabulary you want to use when processing your medical transcription job. Custom vocabulary names are case sensitive.

    The language of the specified custom vocabulary must match the language code that you specify in your transcription request. If the languages do not match, the custom vocabulary isn't applied. There are no errors or warnings associated with a language mismatch. US English (en-US) is the only valid language for Amazon Transcribe Medical.

    *)
  2. max_alternatives : int option;
    (*

    Indicate the maximum number of alternative transcriptions you want Amazon Transcribe Medical to include in your transcript.

    If you select a number greater than the number of alternative transcriptions generated by Amazon Transcribe Medical, only the actual number of alternative transcriptions are included.

    If you include MaxAlternatives in your request, you must also include ShowAlternatives with a value of true.

    For more information, see Alternative transcriptions.

    *)
  3. show_alternatives : bool option;
    (*

    To include alternative transcriptions within your transcription output, include ShowAlternatives in your transcription request.

    If you include ShowAlternatives, you must also include MaxAlternatives, which is the maximum number of alternative transcriptions you want Amazon Transcribe Medical to generate.

    For more information, see Alternative transcriptions.

    *)
  4. channel_identification : bool option;
    (*

    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 does not separate the speech by channel.

    For more information, see Transcribing multi-channel audio.

    *)
  5. max_speaker_labels : int option;
    (*

    Specify the maximum number of speakers you want to partition in your media.

    Note that if your media contains more speakers than the specified number, multiple speakers are treated as a single speaker.

    If you specify the MaxSpeakerLabels field, you must set the ShowSpeakerLabels field to true.

    *)
  6. show_speaker_labels : bool option;
    (*

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

    If you enable ShowSpeakerLabels in your request, you must also include MaxSpeakerLabels.

    For more information, see Partitioning speakers (diarization).

    *)
}

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.

type medical_content_identification_type =
  1. | PHI
type specialty =
  1. | PRIMARYCARE
type medical_transcription_job = {
  1. tags : tag list option;
    (*

    The tags, each in the form of a key:value pair, assigned to the specified medical transcription job.

    *)
  2. type_ : type_ option;
    (*

    Indicates whether the input media is a dictation or a conversation, as specified in the StartMedicalTranscriptionJob request.

    *)
  3. specialty : specialty option;
    (*

    Describes the medical specialty represented in your media.

    *)
  4. content_identification_type : medical_content_identification_type option;
    (*

    Indicates whether content identification was enabled for your transcription request.

    *)
  5. settings : medical_transcription_setting option;
    (*

    Provides information on any additional settings that were included in your request. Additional settings include channel identification, alternative transcriptions, speaker partitioning, custom vocabularies, and custom vocabulary filters.

    *)
  6. failure_reason : string option;
    (*

    If TranscriptionJobStatus is FAILED, FailureReason contains information about why the transcription job request failed.

    The FailureReason field contains one of the following values:

    • Unsupported media format.

      The media format specified in MediaFormat isn't valid. Refer to refer to the MediaFormat parameter for a list of supported formats.

    • The media format provided does not match the detected media format.

      The media format specified in MediaFormat doesn't match the format of the input file. Check the media format of your media file and correct the specified value.

    • Invalid sample rate for audio file.

      The sample rate specified in MediaSampleRateHertz isn't valid. The sample rate must be between 16,000 and 48,000 hertz.

    • The sample rate provided does not match the detected sample rate.

      The sample rate specified in MediaSampleRateHertz doesn't match the sample rate detected in your input media file. Check the sample rate of your media file and correct the specified value.

    • Invalid file size: file size too large.

      The size of your media file is larger than what Amazon Transcribe can process. For more information, refer to Service quotas.

    • Invalid number of channels: number of channels too large.

      Your audio contains more channels than Amazon Transcribe is able to process. For more information, refer to Service quotas.

    *)
  7. completion_time : float option;
    (*

    The date and time the specified medical transcription job finished processing.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:33:13.922000-07:00 represents a transcription job that started processing at 12:33 PM UTC-7 on May 4, 2022.

    *)
  8. creation_time : float option;
    (*

    The date and time the specified medical transcription job request was made.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents a transcription job that started processing at 12:32 PM UTC-7 on May 4, 2022.

    *)
  9. start_time : float option;
    (*

    The date and time the specified medical transcription job began processing.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.789000-07:00 represents a transcription job that started processing at 12:32 PM UTC-7 on May 4, 2022.

    *)
  10. transcript : medical_transcript option;
    (*

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

    *)
  11. media : media option;
  12. media_format : media_format option;
    (*

    The format of the input media file.

    *)
  13. media_sample_rate_hertz : int option;
    (*

    The sample rate, in hertz, of the audio track in your input media file.

    *)
  14. language_code : language_code option;
    (*

    The language code used to create your medical transcription job. US English (en-US) is the only supported language for medical transcriptions.

    *)
  15. transcription_job_status : transcription_job_status option;
    (*

    Provides the status of the specified medical transcription job.

    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.

    *)
  16. medical_transcription_job_name : string option;
    (*

    The name of the medical transcription job. Job names are case sensitive and must be unique within an Amazon Web Services account.

    *)
}

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.

type start_medical_transcription_job_response = {
  1. medical_transcription_job : medical_transcription_job option;
    (*

    Provides detailed information about the current medical transcription job, including job status and, if applicable, failure reason.

    *)
}
type start_medical_transcription_job_request = {
  1. tags : tag list option;
    (*

    Adds one or more custom tags, each in the form of a key:value pair, to a new medical transcription job at the time you start this new job.

    To learn more about using tags with Amazon Transcribe, refer to Tagging resources.

    *)
  2. type_ : type_;
    (*

    Specify whether your input media contains only one person (DICTATION) or contains a conversation between two people (CONVERSATION).

    For example, DICTATION could be used for a medical professional wanting to transcribe voice memos; CONVERSATION could be used for transcribing the doctor-patient dialogue during the patient's office visit.

    *)
  3. specialty : specialty;
    (*

    Specify the predominant medical specialty represented in your media. For batch transcriptions, PRIMARYCARE is the only valid value. If you require additional specialties, refer to .

    *)
  4. content_identification_type : medical_content_identification_type option;
    (*

    Labels all personal health information (PHI) identified in your transcript. For more information, see Identifying personal health information (PHI) in a transcription.

    *)
  5. settings : medical_transcription_setting option;
    (*

    Specify 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.

    *)
  6. kms_encryption_context : (string * string) list option;
    (*

    A map of plain text, non-secret key:value pairs, known as encryption context pairs, that provide an added layer of security for your data. For more information, see KMS encryption context and Asymmetric keys in KMS.

    *)
  7. output_encryption_kms_key_id : string option;
    (*

    The KMS key you want to use to encrypt your medical transcription output.

    If using a key located in the current Amazon Web Services account, you can specify your KMS key in one of four ways:

    1. Use the KMS key ID itself. For example, 1234abcd-12ab-34cd-56ef-1234567890ab.
    2. Use an alias for the KMS key ID. For example, alias/ExampleAlias.
    3. Use the Amazon Resource Name (ARN) for the KMS key ID. For example, arn:aws:kms:region:account-ID:key/1234abcd-12ab-34cd-56ef-1234567890ab.
    4. Use the ARN for the KMS key alias. For example, arn:aws:kms:region:account-ID:alias/ExampleAlias.

    If using a key located in a different Amazon Web Services account than the current Amazon Web Services account, you can specify your KMS key in one of two ways:

    1. Use the ARN for the KMS key ID. For example, arn:aws:kms:region:account-ID:key/1234abcd-12ab-34cd-56ef-1234567890ab.
    2. Use the ARN for the KMS key alias. For example, arn:aws:kms:region:account-ID:alias/ExampleAlias.

    If you do not specify an encryption key, your output is encrypted with the default Amazon S3 key (SSE-S3).

    If you specify a KMS key to encrypt your output, you must also specify an output location using the OutputLocation parameter.

    Note that the role making the request must have permission to use the specified KMS key.

    *)
  8. output_key : string option;
    (*

    Use in combination with OutputBucketName to specify the output location of your transcript and, optionally, a unique name for your output file. The default name for your transcription output is the same as the name you specified for your medical transcription job (MedicalTranscriptionJobName).

    Here are some examples of how you can use OutputKey:

    • If you specify 'DOC-EXAMPLE-BUCKET' as the OutputBucketName and 'my-transcript.json' as the OutputKey, your transcription output path is s3://DOC-EXAMPLE-BUCKET/my-transcript.json.
    • If you specify 'my-first-transcription' as the MedicalTranscriptionJobName, 'DOC-EXAMPLE-BUCKET' as the OutputBucketName, and 'my-transcript' as the OutputKey, your transcription output path is s3://DOC-EXAMPLE-BUCKET/my-transcript/my-first-transcription.json.
    • If you specify 'DOC-EXAMPLE-BUCKET' as the OutputBucketName and 'test-files/my-transcript.json' as the OutputKey, your transcription output path is s3://DOC-EXAMPLE-BUCKET/test-files/my-transcript.json.
    • If you specify 'my-first-transcription' as the MedicalTranscriptionJobName, 'DOC-EXAMPLE-BUCKET' as the OutputBucketName, and 'test-files/my-transcript' as the OutputKey, your transcription output path is s3://DOC-EXAMPLE-BUCKET/test-files/my-transcript/my-first-transcription.json.

    If you specify the name of an Amazon S3 bucket sub-folder that doesn't exist, one is created for you.

    *)
  9. output_bucket_name : string;
    (*

    The name of the Amazon S3 bucket where you want your medical transcription output stored. Do not include the S3:// prefix of the specified bucket.

    If you want your output to go to a sub-folder of this bucket, specify it using the OutputKey parameter; OutputBucketName only accepts the name of a bucket.

    For example, if you want your output stored in S3://DOC-EXAMPLE-BUCKET, set OutputBucketName to DOC-EXAMPLE-BUCKET. However, if you want your output stored in S3://DOC-EXAMPLE-BUCKET/test-files/, set OutputBucketName to DOC-EXAMPLE-BUCKET and OutputKey to test-files/.

    Note that Amazon Transcribe must have permission to use the specified location. You can change Amazon S3 permissions using the Amazon Web Services Management Console. See also Permissions Required for IAM User Roles.

    *)
  10. media : media;
  11. media_format : media_format option;
    (*

    Specify the format of your input media file.

    *)
  12. media_sample_rate_hertz : int option;
    (*

    The sample rate, in hertz, of the audio track in your input media file.

    If you do not specify the media sample rate, Amazon Transcribe Medical determines it for you. If you specify the sample rate, it must match the rate detected by Amazon Transcribe Medical; if there's a mismatch between the value that you specify and the value detected, your job fails. Therefore, in most cases, it's advised to omit MediaSampleRateHertz and let Amazon Transcribe Medical determine the sample rate.

    *)
  13. language_code : language_code;
    (*

    The language code that represents the language spoken in the input media file. US English (en-US) is the only valid value for medical transcription jobs. Any other value you enter for language code results in a BadRequestException error.

    *)
  14. medical_transcription_job_name : string;
    (*

    A unique name, chosen by you, for your medical transcription job. The name that you specify is also used as the default name of your transcription output file. If you want to specify a different name for your transcription output, use the OutputKey parameter.

    This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account. If you try to create a new job with the same name as an existing job, you get a ConflictException error.

    *)
}
type medical_scribe_job_status =
  1. | COMPLETED
  2. | FAILED
  3. | IN_PROGRESS
  4. | QUEUED
type medical_scribe_language_code =
  1. | EN_US
type medical_scribe_output = {
  1. clinical_document_uri : string;
    (*

    Holds the Amazon S3 URI for the Clinical Document.

    *)
  2. transcript_file_uri : string;
    (*

    Holds the Amazon S3 URI for the Transcript.

    *)
}

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.

type medical_scribe_settings = {
  1. vocabulary_filter_method : vocabulary_filter_method option;
    (*

    Specify how you want your custom 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.

    *)
  2. vocabulary_filter_name : string option;
    (*

    The name of the custom vocabulary filter you want to include in your Medical Scribe request. Custom vocabulary filter names are case sensitive.

    Note that if you include VocabularyFilterName in your request, you must also include VocabularyFilterMethod.

    *)
  3. vocabulary_name : string option;
    (*

    The name of the custom vocabulary you want to include in your Medical Scribe request. Custom vocabulary names are case sensitive.

    *)
  4. channel_identification : bool option;
    (*

    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.

    For more information, see Transcribing multi-channel audio.

    *)
  5. max_speaker_labels : int option;
    (*

    Specify the maximum number of speakers you want to partition in your media.

    Note that if your media contains more speakers than the specified number, multiple speakers are treated as a single speaker.

    If you specify the MaxSpeakerLabels field, you must set the ShowSpeakerLabels field to true.

    *)
  6. show_speaker_labels : bool option;
    (*

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

    If you enable ShowSpeakerLabels in your request, you must also include MaxSpeakerLabels.

    For more information, see Partitioning speakers (diarization).

    *)
}

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.

type medical_scribe_participant_role =
  1. | CLINICIAN
  2. | PATIENT
type medical_scribe_channel_definition = {
  1. participant_role : medical_scribe_participant_role;
    (*

    Specify the participant that you want to flag. The options are CLINICIAN and PATIENT

    *)
  2. channel_id : int;
    (*

    Specify the audio channel you want to define.

    *)
}

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

type medical_scribe_job = {
  1. tags : tag list option;
    (*

    Adds one or more custom tags, each in the form of a key:value pair, to the Medica Scribe job.

    To learn more about using tags with Amazon Transcribe, refer to Tagging resources.

    *)
  2. channel_definitions : medical_scribe_channel_definition list option;
    (*

    Makes it possible to specify which speaker is on which channel. For example, if the clinician is the first participant to speak, you would set ChannelId of the first ChannelDefinition in the list to 0 (to indicate the first channel) and ParticipantRole to CLINICIAN (to indicate that it's the clinician speaking). Then you would set the ChannelId of the second ChannelDefinition in the list to 1 (to indicate the second channel) and ParticipantRole to PATIENT (to indicate that it's the patient speaking).

    *)
  3. data_access_role_arn : string option;
    (*

    The Amazon Resource Name (ARN) of an IAM role that has permissions to access the Amazon S3 bucket that contains your input files, write to the output bucket, and use your KMS key if supplied. If the role that you specify doesn’t have the appropriate permissions your request fails.

    IAM role ARNs have the format arn:partition:iam::account:role/role-name-with-path. For example: arn:aws:iam::111122223333:role/Admin.

    For more information, see IAM ARNs.

    *)
  4. settings : medical_scribe_settings option;
    (*

    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.

    *)
  5. failure_reason : string option;
    (*

    If MedicalScribeJobStatus is FAILED, FailureReason contains information about why the transcription job failed. See also: Common Errors.

    *)
  6. completion_time : float option;
    (*

    The date and time the specified Medical Scribe job finished processing.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents a Medical Scribe job that finished processing at 12:32 PM UTC-7 on May 4, 2022.

    *)
  7. creation_time : float option;
    (*

    The date and time the specified Medical Scribe job request was made.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents a Medical Scribe job that started processing at 12:32 PM UTC-7 on May 4, 2022.

    *)
  8. start_time : float option;
    (*

    The date and time your Medical Scribe job began processing.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.789000-07:00 represents a Medical Scribe job that started processing at 12:32 PM UTC-7 on May 4, 2022.

    *)
  9. medical_scribe_output : medical_scribe_output option;
    (*

    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.

    *)
  10. media : media option;
  11. language_code : medical_scribe_language_code option;
    (*

    The language code used to create your Medical Scribe job. US English (en-US) is the only supported language for Medical Scribe jobs.

    *)
  12. medical_scribe_job_status : medical_scribe_job_status option;
    (*

    Provides the status of the specified Medical Scribe job.

    If the status is COMPLETED, the job is finished and 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.

    *)
  13. medical_scribe_job_name : string option;
    (*

    The name of the Medical Scribe job. Job names are case sensitive and must be unique within an Amazon Web Services account.

    *)
}

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.

type start_medical_scribe_job_response = {
  1. medical_scribe_job : medical_scribe_job option;
    (*

    Provides detailed information about the current Medical Scribe job, including job status and, if applicable, failure reason.

    *)
}
type start_medical_scribe_job_request = {
  1. tags : tag list option;
    (*

    Adds one or more custom tags, each in the form of a key:value pair, to the Medica Scribe job.

    To learn more about using tags with Amazon Transcribe, refer to Tagging resources.

    *)
  2. channel_definitions : medical_scribe_channel_definition list option;
    (*

    Makes it possible to specify which speaker is on which channel. For example, if the clinician is the first participant to speak, you would set ChannelId of the first ChannelDefinition in the list to 0 (to indicate the first channel) and ParticipantRole to CLINICIAN (to indicate that it's the clinician speaking). Then you would set the ChannelId of the second ChannelDefinition in the list to 1 (to indicate the second channel) and ParticipantRole to PATIENT (to indicate that it's the patient speaking).

    *)
  3. settings : medical_scribe_settings;
    (*

    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.

    *)
  4. data_access_role_arn : string;
    (*

    The Amazon Resource Name (ARN) of an IAM role that has permissions to access the Amazon S3 bucket that contains your input files, write to the output bucket, and use your KMS key if supplied. If the role that you specify doesn’t have the appropriate permissions your request fails.

    IAM role ARNs have the format arn:partition:iam::account:role/role-name-with-path. For example: arn:aws:iam::111122223333:role/Admin.

    For more information, see IAM ARNs.

    *)
  5. kms_encryption_context : (string * string) list option;
    (*

    A map of plain text, non-secret key:value pairs, known as encryption context pairs, that provide an added layer of security for your data. For more information, see KMS encryption context and Asymmetric keys in KMS.

    *)
  6. output_encryption_kms_key_id : string option;
    (*

    The KMS key you want to use to encrypt your Medical Scribe output.

    If using a key located in the current Amazon Web Services account, you can specify your KMS key in one of four ways:

    1. Use the KMS key ID itself. For example, 1234abcd-12ab-34cd-56ef-1234567890ab.
    2. Use an alias for the KMS key ID. For example, alias/ExampleAlias.
    3. Use the Amazon Resource Name (ARN) for the KMS key ID. For example, arn:aws:kms:region:account-ID:key/1234abcd-12ab-34cd-56ef-1234567890ab.
    4. Use the ARN for the KMS key alias. For example, arn:aws:kms:region:account-ID:alias/ExampleAlias.

    If using a key located in a different Amazon Web Services account than the current Amazon Web Services account, you can specify your KMS key in one of two ways:

    1. Use the ARN for the KMS key ID. For example, arn:aws:kms:region:account-ID:key/1234abcd-12ab-34cd-56ef-1234567890ab.
    2. Use the ARN for the KMS key alias. For example, arn:aws:kms:region:account-ID:alias/ExampleAlias.

    If you do not specify an encryption key, your output is encrypted with the default Amazon S3 key (SSE-S3).

    Note that the role specified in the DataAccessRoleArn request parameter must have permission to use the specified KMS key.

    *)
  7. output_bucket_name : string;
    (*

    The name of the Amazon S3 bucket where you want your Medical Scribe output stored. Do not include the S3:// prefix of the specified bucket.

    Note that the role specified in the DataAccessRoleArn request parameter must have permission to use the specified location. You can change Amazon S3 permissions using the Amazon Web Services Management Console. See also Permissions Required for IAM User Roles.

    *)
  8. media : media;
  9. medical_scribe_job_name : string;
    (*

    A unique name, chosen by you, for your Medical Scribe job.

    This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account. If you try to create a new job with the same name as an existing job, you get a ConflictException error.

    *)
}
type call_analytics_job_status =
  1. | COMPLETED
  2. | FAILED
  3. | IN_PROGRESS
  4. | QUEUED
type call_analytics_feature =
  1. | GENERATIVE_SUMMARIZATION
type call_analytics_skipped_reason_code =
  1. | FAILED_SAFETY_GUIDELINES
  2. | INSUFFICIENT_CONVERSATION_CONTENT
type call_analytics_skipped_feature = {
  1. message : string option;
    (*

    Contains additional information or a message explaining why a specific analytics feature was skipped during the analysis of a call analytics job.

    *)
  2. reason_code : call_analytics_skipped_reason_code option;
    (*

    Provides a code indicating the reason why a specific analytics feature was skipped during the analysis of a call analytics job.

    *)
  3. feature : call_analytics_feature option;
    (*

    Indicates the type of analytics feature that was skipped during the analysis of a call analytics job.

    *)
}

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.

type call_analytics_job_details = {
  1. skipped : call_analytics_skipped_feature list option;
    (*

    Contains information about any skipped analytics features during the analysis of a call analytics job.

    This array lists all the analytics features that were skipped, along with their corresponding reason code and message.

    *)
}

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

type summarization = {
  1. generate_abstractive_summary : bool;
    (*

    Enables Generative call summarization in your Call Analytics request

    Generative call summarization provides a summary of the transcript including important components discussed in the conversation.

    For more information, see Enabling generative call summarization.

    *)
}

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

type call_analytics_job_settings = {
  1. summarization : summarization option;
    (*

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

    *)
  2. language_id_settings : (string * language_id_settings) list option;
    (*

    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).

    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, custom vocabulary, or custom vocabulary filter with your request but do not want to use automatic language identification, use instead the parameter with the LanguageModelName, VocabularyName, or VocabularyFilterName sub-parameters.

    For a list of languages supported with Call Analytics, refer to Supported languages and language-specific features.

    *)
  3. language_options : language_code list option;
    (*

    You can 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.

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

    To transcribe speech in Modern Standard Arabic (ar-SA), your media file must be encoded at a sample rate of 16,000 Hz or higher.

    *)
  4. content_redaction : content_redaction option;
  5. language_model_name : string option;
    (*

    The name of the custom language model you want to use when processing your Call Analytics job. Note that custom language model names are case sensitive.

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

    *)
  6. vocabulary_filter_method : vocabulary_filter_method option;
    (*

    Specify how you want your custom 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.

    *)
  7. vocabulary_filter_name : string option;
    (*

    The name of the custom vocabulary filter you want to include in your Call Analytics transcription request. Custom vocabulary filter names are case sensitive.

    Note that if you include VocabularyFilterName in your request, you must also include VocabularyFilterMethod.

    *)
  8. vocabulary_name : string option;
    (*

    The name of the custom vocabulary you want to include in your Call Analytics transcription request. Custom vocabulary names are case sensitive.

    *)
}

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.

type channel_definition = {
  1. participant_role : participant_role option;
    (*

    Specify the speaker you want to define. Omitting this parameter is equivalent to specifying both participants.

    *)
  2. channel_id : int option;
    (*

    Specify the audio channel you want to define.

    *)
}

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).

type call_analytics_job = {
  1. channel_definitions : channel_definition list option;
    (*

    Indicates which speaker is on which channel.

    *)
  2. settings : call_analytics_job_settings option;
    (*

    Provides information on any additional settings that were included in your request. Additional settings include content redaction and language identification settings.

    *)
  3. identified_language_score : float option;
    (*

    The confidence score associated with the language identified in your media file.

    Confidence scores are values between 0 and 1; a larger value indicates a higher probability that the identified language correctly matches the language spoken in your media.

    *)
  4. data_access_role_arn : string option;
    (*

    The Amazon Resource Name (ARN) you included in your request.

    *)
  5. failure_reason : string option;
    (*

    If CallAnalyticsJobStatus is FAILED, FailureReason contains information about why the Call Analytics job request failed.

    The FailureReason field contains one of the following values:

    • Unsupported media format.

      The media format specified in MediaFormat isn't valid. Refer to refer to the MediaFormat parameter for a list of supported formats.

    • The media format provided does not match the detected media format.

      The media format specified in MediaFormat doesn't match the format of the input file. Check the media format of your media file and correct the specified value.

    • Invalid sample rate for audio file.

      The sample rate specified in MediaSampleRateHertz isn't valid. The sample rate must be between 8,000 and 48,000 hertz.

    • The sample rate provided does not match the detected sample rate.

      The sample rate specified in MediaSampleRateHertz doesn't match the sample rate detected in your input media file. Check the sample rate of your media file and correct the specified value.

    • Invalid file size: file size too large.

      The size of your media file is larger than what Amazon Transcribe can process. For more information, refer to Service quotas.

    • Invalid number of channels: number of channels too large.

      Your audio contains more channels than Amazon Transcribe is able to process. For more information, refer to Service quotas.

    *)
  6. completion_time : float option;
    (*

    The date and time the specified Call Analytics job finished processing.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:33:13.922000-07:00 represents a transcription job that started processing at 12:33 PM UTC-7 on May 4, 2022.

    *)
  7. creation_time : float option;
    (*

    The date and time the specified Call Analytics job request was made.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents a transcription job that started processing at 12:32 PM UTC-7 on May 4, 2022.

    *)
  8. start_time : float option;
    (*

    The date and time the specified Call Analytics job began processing.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.789000-07:00 represents a transcription job that started processing at 12:32 PM UTC-7 on May 4, 2022.

    *)
  9. transcript : transcript option;
  10. media : media option;
    (*

    Provides the Amazon S3 location of the media file you used in your Call Analytics request.

    *)
  11. media_format : media_format option;
    (*

    The format of the input media file.

    *)
  12. media_sample_rate_hertz : int option;
    (*

    The sample rate, in hertz, of the audio track in your input media file.

    *)
  13. language_code : language_code option;
    (*

    The language code used to create your Call Analytics job. For a list of supported languages and their associated language codes, refer to the Supported languages table.

    If you do not know the language spoken in your media file, you can omit this field and let Amazon Transcribe automatically identify the language of your media. To improve the accuracy of language identification, you can include several language codes and Amazon Transcribe chooses the closest match for your transcription.

    *)
  14. call_analytics_job_details : call_analytics_job_details option;
    (*

    Provides detailed information about a call analytics job, including information about skipped analytics features.

    *)
  15. call_analytics_job_status : call_analytics_job_status option;
    (*

    Provides the status of the specified Call Analytics job.

    If the status is COMPLETED, the job is finished and you can find the results at the location specified in TranscriptFileUri (or RedactedTranscriptFileUri, if you requested transcript redaction). If the status is FAILED, FailureReason provides details on why your transcription job failed.

    *)
  16. call_analytics_job_name : string option;
    (*

    The name of the Call Analytics job. Job names are case sensitive and must be unique within an Amazon Web Services account.

    *)
}

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.

type start_call_analytics_job_response = {
  1. call_analytics_job : call_analytics_job option;
    (*

    Provides detailed information about the current Call Analytics job, including job status and, if applicable, failure reason.

    *)
}
type start_call_analytics_job_request = {
  1. channel_definitions : channel_definition list option;
    (*

    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).

    *)
  2. settings : call_analytics_job_settings option;
    (*

    Specify additional optional settings in your request, including content redaction; allows you to apply custom language models, vocabulary filters, and custom vocabularies to your Call Analytics job.

    *)
  3. data_access_role_arn : string option;
    (*

    The Amazon Resource Name (ARN) of an IAM role that has permissions to access the Amazon S3 bucket that contains your input files. If the role that you specify doesn’t have the appropriate permissions to access the specified Amazon S3 location, your request fails.

    IAM role ARNs have the format arn:partition:iam::account:role/role-name-with-path. For example: arn:aws:iam::111122223333:role/Admin.

    For more information, see IAM ARNs.

    *)
  4. output_encryption_kms_key_id : string option;
    (*

    The KMS key you want to use to encrypt your Call Analytics output.

    If using a key located in the current Amazon Web Services account, you can specify your KMS key in one of four ways:

    1. Use the KMS key ID itself. For example, 1234abcd-12ab-34cd-56ef-1234567890ab.
    2. Use an alias for the KMS key ID. For example, alias/ExampleAlias.
    3. Use the Amazon Resource Name (ARN) for the KMS key ID. For example, arn:aws:kms:region:account-ID:key/1234abcd-12ab-34cd-56ef-1234567890ab.
    4. Use the ARN for the KMS key alias. For example, arn:aws:kms:region:account-ID:alias/ExampleAlias.

    If using a key located in a different Amazon Web Services account than the current Amazon Web Services account, you can specify your KMS key in one of two ways:

    1. Use the ARN for the KMS key ID. For example, arn:aws:kms:region:account-ID:key/1234abcd-12ab-34cd-56ef-1234567890ab.
    2. Use the ARN for the KMS key alias. For example, arn:aws:kms:region:account-ID:alias/ExampleAlias.

    If you do not specify an encryption key, your output is encrypted with the default Amazon S3 key (SSE-S3).

    If you specify a KMS key to encrypt your output, you must also specify an output location using the OutputLocation parameter.

    Note that the role making the request must have permission to use the specified KMS key.

    *)
  5. output_location : string option;
    (*

    The Amazon S3 location where you want your Call Analytics transcription output stored. You can use any of the following formats to specify the output location:

    1. s3://DOC-EXAMPLE-BUCKET
    2. s3://DOC-EXAMPLE-BUCKET/my-output-folder/
    3. s3://DOC-EXAMPLE-BUCKET/my-output-folder/my-call-analytics-job.json

    Unless you specify a file name (option 3), the name of your output file has a default value that matches the name you specified for your transcription job using the CallAnalyticsJobName parameter.

    You can specify a KMS key to encrypt your output using the OutputEncryptionKMSKeyId parameter. If you do not specify a KMS key, Amazon Transcribe uses the default Amazon S3 key for server-side encryption.

    If you do not specify OutputLocation, your transcript is placed in a service-managed Amazon S3 bucket and you are provided with a URI to access your transcript.

    *)
  6. media : media;
    (*

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

    *)
  7. call_analytics_job_name : string;
    (*

    A unique name, chosen by you, for your Call Analytics job.

    This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account. If you try to create a new job with the same name as an existing job, you get a ConflictException error.

    *)
}
type list_vocabulary_filters_response = {
  1. vocabulary_filters : vocabulary_filter_info list option;
    (*

    Provides information about the custom vocabulary filters that match the criteria specified in your request.

    *)
  2. next_token : string option;
    (*

    If NextToken is present in your response, it indicates that not all results are displayed. To view the next set of results, copy the string associated with the NextToken parameter in your results output, then run your request again including NextToken with the value of the copied string. Repeat as needed to view all your results.

    *)
}
type list_vocabulary_filters_request = {
  1. name_contains : string option;
    (*

    Returns only the custom vocabulary filters that contain the specified string. The search is not case sensitive.

    *)
  2. max_results : int option;
    (*

    The maximum number of custom vocabulary filters to return in each page of results. If there are fewer results than the value that you specify, only the actual results are returned. If you do not specify a value, a default of 5 is used.

    *)
  3. next_token : string option;
    (*

    If your ListVocabularyFilters request returns more results than can be displayed, NextToken is displayed in the response with an associated string. To get the next page of results, copy this string and repeat your request, including NextToken with the value of the copied string. Repeat as needed to view all your results.

    *)
}
type list_vocabularies_response = {
  1. vocabularies : vocabulary_info list option;
    (*

    Provides information about the custom vocabularies that match the criteria specified in your request.

    *)
  2. next_token : string option;
    (*

    If NextToken is present in your response, it indicates that not all results are displayed. To view the next set of results, copy the string associated with the NextToken parameter in your results output, then run your request again including NextToken with the value of the copied string. Repeat as needed to view all your results.

    *)
  3. status : vocabulary_state option;
    (*

    Lists all custom vocabularies that have the status specified in your request. Vocabularies are ordered by creation date, with the newest vocabulary first.

    *)
}
type list_vocabularies_request = {
  1. name_contains : string option;
    (*

    Returns only the custom vocabularies that contain the specified string. The search is not case sensitive.

    *)
  2. state_equals : vocabulary_state option;
    (*

    Returns only custom vocabularies with the specified state. Vocabularies are ordered by creation date, with the newest vocabulary first. If you do not include StateEquals, all custom medical vocabularies are returned.

    *)
  3. max_results : int option;
    (*

    The maximum number of custom vocabularies to return in each page of results. If there are fewer results than the value that you specify, only the actual results are returned. If you do not specify a value, a default of 5 is used.

    *)
  4. next_token : string option;
    (*

    If your ListVocabularies request returns more results than can be displayed, NextToken is displayed in the response with an associated string. To get the next page of results, copy this string and repeat your request, including NextToken with the value of the copied string. Repeat as needed to view all your results.

    *)
}
type list_transcription_jobs_response = {
  1. transcription_job_summaries : transcription_job_summary list option;
    (*

    Provides a summary of information about each result.

    *)
  2. next_token : string option;
    (*

    If NextToken is present in your response, it indicates that not all results are displayed. To view the next set of results, copy the string associated with the NextToken parameter in your results output, then run your request again including NextToken with the value of the copied string. Repeat as needed to view all your results.

    *)
  3. status : transcription_job_status option;
    (*

    Lists all transcription jobs that have the status specified in your request. Jobs are ordered by creation date, with the newest job first.

    *)
}
type list_transcription_jobs_request = {
  1. max_results : int option;
    (*

    The maximum number of transcription jobs to return in each page of results. If there are fewer results than the value that you specify, only the actual results are returned. If you do not specify a value, a default of 5 is used.

    *)
  2. next_token : string option;
    (*

    If your ListTranscriptionJobs request returns more results than can be displayed, NextToken is displayed in the response with an associated string. To get the next page of results, copy this string and repeat your request, including NextToken with the value of the copied string. Repeat as needed to view all your results.

    *)
  3. job_name_contains : string option;
    (*

    Returns only the transcription jobs that contain the specified string. The search is not case sensitive.

    *)
  4. status : transcription_job_status option;
    (*

    Returns only transcription jobs with the specified status. Jobs are ordered by creation date, with the newest job first. If you do not include Status, all transcription jobs are returned.

    *)
}
type list_tags_for_resource_response = {
  1. tags : tag list option;
    (*

    Lists all tags associated with the given transcription job, vocabulary, model, or resource.

    *)
  2. resource_arn : string option;
    (*

    The Amazon Resource Name (ARN) specified in your request.

    *)
}
type list_tags_for_resource_request = {
  1. resource_arn : string;
    (*

    Returns a list of all tags associated with the specified Amazon Resource Name (ARN). ARNs have the format arn:partition:service:region:account-id:resource-type/resource-id.

    For example, arn:aws:transcribe:us-west-2:111122223333:transcription-job/transcription-job-name.

    Valid values for resource-type are: transcription-job, medical-transcription-job, vocabulary, medical-vocabulary, vocabulary-filter, and language-model.

    *)
}
type list_medical_vocabularies_response = {
  1. vocabularies : vocabulary_info list option;
    (*

    Provides information about the custom medical vocabularies that match the criteria specified in your request.

    *)
  2. next_token : string option;
    (*

    If NextToken is present in your response, it indicates that not all results are displayed. To view the next set of results, copy the string associated with the NextToken parameter in your results output, then run your request again including NextToken with the value of the copied string. Repeat as needed to view all your results.

    *)
  3. status : vocabulary_state option;
    (*

    Lists all custom medical vocabularies that have the status specified in your request. Custom vocabularies are ordered by creation date, with the newest vocabulary first.

    *)
}
type list_medical_vocabularies_request = {
  1. name_contains : string option;
    (*

    Returns only the custom medical vocabularies that contain the specified string. The search is not case sensitive.

    *)
  2. state_equals : vocabulary_state option;
    (*

    Returns only custom medical vocabularies with the specified state. Custom vocabularies are ordered by creation date, with the newest vocabulary first. If you do not include StateEquals, all custom medical vocabularies are returned.

    *)
  3. max_results : int option;
    (*

    The maximum number of custom medical vocabularies to return in each page of results. If there are fewer results than the value that you specify, only the actual results are returned. If you do not specify a value, a default of 5 is used.

    *)
  4. next_token : string option;
    (*

    If your ListMedicalVocabularies request returns more results than can be displayed, NextToken is displayed in the response with an associated string. To get the next page of results, copy this string and repeat your request, including NextToken with the value of the copied string. Repeat as needed to view all your results.

    *)
}
type medical_transcription_job_summary = {
  1. type_ : type_ option;
    (*

    Indicates whether the input media is a dictation or a conversation, as specified in the StartMedicalTranscriptionJob request.

    *)
  2. content_identification_type : medical_content_identification_type option;
    (*

    Labels all personal health information (PHI) identified in your transcript. For more information, see Identifying personal health information (PHI) in a transcription.

    *)
  3. specialty : specialty option;
    (*

    Provides the medical specialty represented in your media.

    *)
  4. output_location_type : output_location_type option;
    (*

    Indicates where the specified medical transcription output is stored.

    If the value is CUSTOMER_BUCKET, the location is the Amazon S3 bucket you specified using the OutputBucketName parameter in your request. If you also included OutputKey in your request, your output is located in the path you specified in your request.

    If the value is SERVICE_BUCKET, the location is a service-managed Amazon S3 bucket. To access a transcript stored in a service-managed bucket, use the URI shown in the TranscriptFileUri field.

    *)
  5. failure_reason : string option;
    (*

    If TranscriptionJobStatus is FAILED, FailureReason contains information about why the transcription job failed. See also: Common Errors.

    *)
  6. transcription_job_status : transcription_job_status option;
    (*

    Provides the status of your medical transcription job.

    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.

    *)
  7. language_code : language_code option;
    (*

    The language code used to create your medical transcription. US English (en-US) is the only supported language for medical transcriptions.

    *)
  8. completion_time : float option;
    (*

    The date and time the specified medical transcription job finished processing.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:33:13.922000-07:00 represents a transcription job that started processing at 12:33 PM UTC-7 on May 4, 2022.

    *)
  9. start_time : float option;
    (*

    The date and time your medical transcription job began processing.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.789000-07:00 represents a transcription job that started processing at 12:32 PM UTC-7 on May 4, 2022.

    *)
  10. creation_time : float option;
    (*

    The date and time the specified medical transcription job request was made.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents a transcription job that started processing at 12:32 PM UTC-7 on May 4, 2022.

    *)
  11. medical_transcription_job_name : string option;
    (*

    The name of the medical transcription job. Job names are case sensitive and must be unique within an Amazon Web Services account.

    *)
}

Provides detailed information about a specific medical transcription job.

type list_medical_transcription_jobs_response = {
  1. medical_transcription_job_summaries : medical_transcription_job_summary list option;
    (*

    Provides a summary of information about each result.

    *)
  2. next_token : string option;
    (*

    If NextToken is present in your response, it indicates that not all results are displayed. To view the next set of results, copy the string associated with the NextToken parameter in your results output, then run your request again including NextToken with the value of the copied string. Repeat as needed to view all your results.

    *)
  3. status : transcription_job_status option;
    (*

    Lists all medical transcription jobs that have the status specified in your request. Jobs are ordered by creation date, with the newest job first.

    *)
}
type list_medical_transcription_jobs_request = {
  1. max_results : int option;
    (*

    The maximum number of medical transcription jobs to return in each page of results. If there are fewer results than the value that you specify, only the actual results are returned. If you do not specify a value, a default of 5 is used.

    *)
  2. next_token : string option;
    (*

    If your ListMedicalTranscriptionJobs request returns more results than can be displayed, NextToken is displayed in the response with an associated string. To get the next page of results, copy this string and repeat your request, including NextToken with the value of the copied string. Repeat as needed to view all your results.

    *)
  3. job_name_contains : string option;
    (*

    Returns only the medical transcription jobs that contain the specified string. The search is not case sensitive.

    *)
  4. status : transcription_job_status option;
    (*

    Returns only medical transcription jobs with the specified status. Jobs are ordered by creation date, with the newest job first. If you do not include Status, all medical transcription jobs are returned.

    *)
}
type medical_scribe_job_summary = {
  1. failure_reason : string option;
    (*

    If MedicalScribeJobStatus is FAILED, FailureReason contains information about why the transcription job failed. See also: Common Errors.

    *)
  2. medical_scribe_job_status : medical_scribe_job_status option;
    (*

    Provides the status of the specified Medical Scribe job.

    If the status is COMPLETED, the job is finished and 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.

    *)
  3. language_code : medical_scribe_language_code option;
    (*

    The language code used to create your Medical Scribe job. US English (en-US) is the only supported language for Medical Scribe jobs.

    *)
  4. completion_time : float option;
    (*

    The date and time the specified Medical Scribe job finished processing.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents a Medical Scribe job that finished processing at 12:32 PM UTC-7 on May 4, 2022.

    *)
  5. start_time : float option;
    (*

    The date and time your Medical Scribe job began processing.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.789000-07:00 represents a Medical Scribe job that started processing at 12:32 PM UTC-7 on May 4, 2022.

    *)
  6. creation_time : float option;
    (*

    The date and time the specified Medical Scribe job request was made.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents a Medical Scribe job that started processing at 12:32 PM UTC-7 on May 4, 2022.

    *)
  7. medical_scribe_job_name : string option;
    (*

    The name of the Medical Scribe job. Job names are case sensitive and must be unique within an Amazon Web Services account.

    *)
}

Provides detailed information about a specific Medical Scribe job.

type list_medical_scribe_jobs_response = {
  1. medical_scribe_job_summaries : medical_scribe_job_summary list option;
    (*

    Provides a summary of information about each result.

    *)
  2. next_token : string option;
    (*

    If NextToken is present in your response, it indicates that not all results are displayed. To view the next set of results, copy the string associated with the NextToken parameter in your results output, then run your request again including NextToken with the value of the copied string. Repeat as needed to view all your results.

    *)
  3. status : medical_scribe_job_status option;
    (*

    Lists all Medical Scribe jobs that have the status specified in your request. Jobs are ordered by creation date, with the newest job first.

    *)
}
type list_medical_scribe_jobs_request = {
  1. max_results : int option;
    (*

    The maximum number of Medical Scribe jobs to return in each page of results. If there are fewer results than the value that you specify, only the actual results are returned. If you do not specify a value, a default of 5 is used.

    *)
  2. next_token : string option;
    (*

    If your ListMedicalScribeJobs request returns more results than can be displayed, NextToken is displayed in the response with an associated string. To get the next page of results, copy this string and repeat your request, including NextToken with the value of the copied string. Repeat as needed to view all your results.

    *)
  3. job_name_contains : string option;
    (*

    Returns only the Medical Scribe jobs that contain the specified string. The search is not case sensitive.

    *)
  4. status : medical_scribe_job_status option;
    (*

    Returns only Medical Scribe jobs with the specified status. Jobs are ordered by creation date, with the newest job first. If you do not include Status, all Medical Scribe jobs are returned.

    *)
}
type clm_language_code =
  1. | JA_JP
  2. | DE_DE
  3. | EN_AU
  4. | EN_GB
  5. | ES_US
  6. | HI_IN
  7. | EN_US
type base_model_name =
  1. | WIDE_BAND
  2. | NARROW_BAND
type model_status =
  1. | COMPLETED
  2. | FAILED
  3. | IN_PROGRESS
type input_data_config = {
  1. data_access_role_arn : string;
    (*

    The Amazon Resource Name (ARN) of an IAM role that has permissions to access the Amazon S3 bucket that contains your input files. If the role that you specify doesn’t have the appropriate permissions to access the specified Amazon S3 location, your request fails.

    IAM role ARNs have the format arn:partition:iam::account:role/role-name-with-path. For example: arn:aws:iam::111122223333:role/Admin.

    For more information, see IAM ARNs.

    *)
  2. tuning_data_s3_uri : string option;
    (*

    The Amazon S3 location (URI) of the text files you want to use to tune your custom language model.

    Here's an example URI path: s3://DOC-EXAMPLE-BUCKET/my-model-tuning-data/

    *)
  3. s3_uri : string;
    (*

    The Amazon S3 location (URI) of the text files you want to use to train your custom language model.

    Here's an example URI path: s3://DOC-EXAMPLE-BUCKET/my-model-training-data/

    *)
}

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.

type language_model = {
  1. input_data_config : input_data_config option;
    (*

    The Amazon S3 location of the input files used to train and tune your custom language model, in addition to the data access role ARN (Amazon Resource Name) that has permissions to access these data.

    *)
  2. failure_reason : string option;
    (*

    If ModelStatus is FAILED, FailureReason contains information about why the custom language model request failed. See also: Common Errors.

    *)
  3. upgrade_availability : bool option;
    (*

    Shows if a more current base model is available for use with the specified custom language model.

    If false, your custom language model is using the most up-to-date base model.

    If true, there is a newer base model available than the one your language model is using.

    Note that to update a base model, you must recreate the custom language model using the new base model. Base model upgrades for existing custom language models are not supported.

    *)
  4. model_status : model_status option;
    (*

    The status of the specified custom language model. When the status displays as COMPLETED the model is ready for use.

    *)
  5. base_model_name : base_model_name option;
    (*

    The Amazon Transcribe standard language model, or base model, used to create your custom language model.

    *)
  6. language_code : clm_language_code option;
    (*

    The language code used to create your custom language model. Each custom language model must contain terms in only one language, and the language you select for your custom language model must match the language of your training and tuning data.

    For a list of supported languages and their associated language codes, refer to the Supported languages table. Note that US English (en-US) is the only language supported with Amazon Transcribe Medical.

    *)
  7. last_modified_time : float option;
    (*

    The date and time the specified custom language model was last modified.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents 12:32 PM UTC-7 on May 4, 2022.

    *)
  8. create_time : float option;
    (*

    The date and time the specified custom language model was created.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents 12:32 PM UTC-7 on May 4, 2022.

    *)
  9. model_name : string option;
    (*

    A unique name, chosen by you, for your custom language model.

    This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account.

    *)
}

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
type list_language_models_response = {
  1. models : language_model list option;
    (*

    Provides information about the custom language models that match the criteria specified in your request.

    *)
  2. next_token : string option;
    (*

    If NextToken is present in your response, it indicates that not all results are displayed. To view the next set of results, copy the string associated with the NextToken parameter in your results output, then run your request again including NextToken with the value of the copied string. Repeat as needed to view all your results.

    *)
}
type list_language_models_request = {
  1. max_results : int option;
    (*

    The maximum number of custom language models to return in each page of results. If there are fewer results than the value that you specify, only the actual results are returned. If you do not specify a value, a default of 5 is used.

    *)
  2. next_token : string option;
    (*

    If your ListLanguageModels request returns more results than can be displayed, NextToken is displayed in the response with an associated string. To get the next page of results, copy this string and repeat your request, including NextToken with the value of the copied string. Repeat as needed to view all your results.

    *)
  3. name_contains : string option;
    (*

    Returns only the custom language models that contain the specified string. The search is not case sensitive.

    *)
  4. status_equals : model_status option;
    (*

    Returns only custom language models with the specified status. Language models are ordered by creation date, with the newest model first. If you do not include StatusEquals, all custom language models are returned.

    *)
}
type call_analytics_job_summary = {
  1. failure_reason : string option;
    (*

    If CallAnalyticsJobStatus is FAILED, FailureReason contains information about why the Call Analytics job failed. See also: Common Errors.

    *)
  2. call_analytics_job_details : call_analytics_job_details option;
    (*

    Provides detailed information about a call analytics job, including information about skipped analytics features.

    *)
  3. call_analytics_job_status : call_analytics_job_status option;
    (*

    Provides the status of your Call Analytics job.

    If the status is COMPLETED, the job is finished and you can find the results at the location specified in TranscriptFileUri (or RedactedTranscriptFileUri, if you requested transcript redaction). If the status is FAILED, FailureReason provides details on why your transcription job failed.

    *)
  4. language_code : language_code option;
    (*

    The language code used to create your Call Analytics transcription.

    *)
  5. completion_time : float option;
    (*

    The date and time the specified Call Analytics job finished processing.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:33:13.922000-07:00 represents a transcription job that started processing at 12:33 PM UTC-7 on May 4, 2022.

    *)
  6. start_time : float option;
    (*

    The date and time your Call Analytics job began processing.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.789000-07:00 represents a transcription job that started processing at 12:32 PM UTC-7 on May 4, 2022.

    *)
  7. creation_time : float option;
    (*

    The date and time the specified Call Analytics job request was made.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents a transcription job that started processing at 12:32 PM UTC-7 on May 4, 2022.

    *)
  8. call_analytics_job_name : string option;
    (*

    The name of the Call Analytics job. Job names are case sensitive and must be unique within an Amazon Web Services account.

    *)
}

Provides detailed information about a specific Call Analytics job.

type list_call_analytics_jobs_response = {
  1. call_analytics_job_summaries : call_analytics_job_summary list option;
    (*

    Provides a summary of information about each result.

    *)
  2. next_token : string option;
    (*

    If NextToken is present in your response, it indicates that not all results are displayed. To view the next set of results, copy the string associated with the NextToken parameter in your results output, then run your request again including NextToken with the value of the copied string. Repeat as needed to view all your results.

    *)
  3. status : call_analytics_job_status option;
    (*

    Lists all Call Analytics jobs that have the status specified in your request. Jobs are ordered by creation date, with the newest job first.

    *)
}
type list_call_analytics_jobs_request = {
  1. max_results : int option;
    (*

    The maximum number of Call Analytics jobs to return in each page of results. If there are fewer results than the value that you specify, only the actual results are returned. If you do not specify a value, a default of 5 is used.

    *)
  2. next_token : string option;
    (*

    If your ListCallAnalyticsJobs request returns more results than can be displayed, NextToken is displayed in the response with an associated string. To get the next page of results, copy this string and repeat your request, including NextToken with the value of the copied string. Repeat as needed to view all your results.

    *)
  3. job_name_contains : string option;
    (*

    Returns only the Call Analytics jobs that contain the specified string. The search is not case sensitive.

    *)
  4. status : call_analytics_job_status option;
    (*

    Returns only Call Analytics jobs with the specified status. Jobs are ordered by creation date, with the newest job first. If you do not include Status, all Call Analytics jobs are returned.

    *)
}
type list_call_analytics_categories_response = {
  1. categories : category_properties list option;
    (*

    Provides detailed information about your Call Analytics categories, including all the rules associated with each category.

    *)
  2. next_token : string option;
    (*

    If NextToken is present in your response, it indicates that not all results are displayed. To view the next set of results, copy the string associated with the NextToken parameter in your results output, then run your request again including NextToken with the value of the copied string. Repeat as needed to view all your results.

    *)
}
type list_call_analytics_categories_request = {
  1. max_results : int option;
    (*

    The maximum number of Call Analytics categories to return in each page of results. If there are fewer results than the value that you specify, only the actual results are returned. If you do not specify a value, a default of 5 is used.

    *)
  2. next_token : string option;
    (*

    If your ListCallAnalyticsCategories request returns more results than can be displayed, NextToken is displayed in the response with an associated string. To get the next page of results, copy this string and repeat your request, including NextToken with the value of the copied string. Repeat as needed to view all your results.

    *)
}
type get_vocabulary_filter_response = {
  1. download_uri : string option;
    (*

    The Amazon S3 location where the custom vocabulary filter is stored; use this URI to view or download the custom vocabulary filter.

    *)
  2. last_modified_time : float option;
    (*

    The date and time the specified custom vocabulary filter was last modified.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents 12:32 PM UTC-7 on May 4, 2022.

    *)
  3. language_code : language_code option;
    (*

    The language code you selected for your custom vocabulary filter.

    *)
  4. vocabulary_filter_name : string option;
    (*

    The name of the custom vocabulary filter you requested information about.

    *)
}
type get_vocabulary_filter_request = {
  1. vocabulary_filter_name : string;
    (*

    The name of the custom vocabulary filter you want information about. Custom vocabulary filter names are case sensitive.

    *)
}
type get_vocabulary_response = {
  1. download_uri : string option;
    (*

    The Amazon S3 location where the custom vocabulary is stored; use this URI to view or download the custom vocabulary.

    *)
  2. failure_reason : string option;
    (*

    If VocabularyState is FAILED, FailureReason contains information about why the custom vocabulary request failed. See also: Common Errors.

    *)
  3. last_modified_time : float option;
    (*

    The date and time the specified custom vocabulary was last modified.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents 12:32 PM UTC-7 on May 4, 2022.

    *)
  4. vocabulary_state : vocabulary_state option;
    (*

    The processing state of your custom vocabulary. If the state is READY, you can use the custom vocabulary in a StartTranscriptionJob request.

    *)
  5. language_code : language_code option;
    (*

    The language code you selected for your custom vocabulary.

    *)
  6. vocabulary_name : string option;
    (*

    The name of the custom vocabulary you requested information about.

    *)
}
type get_vocabulary_request = {
  1. vocabulary_name : string;
    (*

    The name of the custom vocabulary you want information about. Custom vocabulary names are case sensitive.

    *)
}
type get_transcription_job_response = {
  1. transcription_job : transcription_job option;
    (*

    Provides detailed information about the specified transcription job, including job status and, if applicable, failure reason.

    *)
}
type get_transcription_job_request = {
  1. transcription_job_name : string;
    (*

    The name of the transcription job you want information about. Job names are case sensitive.

    *)
}
type get_medical_vocabulary_response = {
  1. download_uri : string option;
    (*

    The Amazon S3 location where the specified custom medical vocabulary is stored; use this URI to view or download the custom vocabulary.

    *)
  2. failure_reason : string option;
    (*

    If VocabularyState is FAILED, FailureReason contains information about why the custom medical vocabulary request failed. See also: Common Errors.

    *)
  3. last_modified_time : float option;
    (*

    The date and time the specified custom medical vocabulary was last modified.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents 12:32 PM UTC-7 on May 4, 2022.

    *)
  4. vocabulary_state : vocabulary_state option;
    (*

    The processing state of your custom medical vocabulary. If the state is READY, you can use the custom vocabulary in a StartMedicalTranscriptionJob request.

    *)
  5. language_code : language_code option;
    (*

    The language code you selected for your custom medical vocabulary. US English (en-US) is the only language supported with Amazon Transcribe Medical.

    *)
  6. vocabulary_name : string option;
    (*

    The name of the custom medical vocabulary you requested information about.

    *)
}
type get_medical_vocabulary_request = {
  1. vocabulary_name : string;
    (*

    The name of the custom medical vocabulary you want information about. Custom medical vocabulary names are case sensitive.

    *)
}
type get_medical_transcription_job_response = {
  1. medical_transcription_job : medical_transcription_job option;
    (*

    Provides detailed information about the specified medical transcription job, including job status and, if applicable, failure reason.

    *)
}
type get_medical_transcription_job_request = {
  1. medical_transcription_job_name : string;
    (*

    The name of the medical transcription job you want information about. Job names are case sensitive.

    *)
}
type get_medical_scribe_job_response = {
  1. medical_scribe_job : medical_scribe_job option;
    (*

    Provides detailed information about the specified Medical Scribe job, including job status and, if applicable, failure reason

    *)
}
type get_medical_scribe_job_request = {
  1. medical_scribe_job_name : string;
    (*

    The name of the Medical Scribe job you want information about. Job names are case sensitive.

    *)
}
type get_call_analytics_job_response = {
  1. call_analytics_job : call_analytics_job option;
    (*

    Provides detailed information about the specified Call Analytics job, including job status and, if applicable, failure reason.

    *)
}
type get_call_analytics_job_request = {
  1. call_analytics_job_name : string;
    (*

    The name of the Call Analytics job you want information about. Job names are case sensitive.

    *)
}
type get_call_analytics_category_response = {
  1. category_properties : category_properties option;
    (*

    Provides you with the properties of the Call Analytics category you specified in your GetCallAnalyticsCategory request.

    *)
}
type get_call_analytics_category_request = {
  1. category_name : string;
    (*

    The name of the Call Analytics category you want information about. Category names are case sensitive.

    *)
}
type describe_language_model_response = {
  1. language_model : language_model option;
    (*

    Provides information about the specified custom language model.

    This parameter also shows if the base language model 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 this DescribeLanguageModel to help identify the reason for this failure.

    *)
}
type describe_language_model_request = {
  1. model_name : string;
    (*

    The name of the custom language model you want information about. Model names are case sensitive.

    *)
}
type delete_vocabulary_filter_request = {
  1. vocabulary_filter_name : string;
    (*

    The name of the custom vocabulary filter you want to delete. Custom vocabulary filter names are case sensitive.

    *)
}
type delete_vocabulary_request = {
  1. vocabulary_name : string;
    (*

    The name of the custom vocabulary you want to delete. Custom vocabulary names are case sensitive.

    *)
}
type delete_transcription_job_request = {
  1. transcription_job_name : string;
    (*

    The name of the transcription job you want to delete. Job names are case sensitive.

    *)
}
type delete_medical_vocabulary_request = {
  1. vocabulary_name : string;
    (*

    The name of the custom medical vocabulary you want to delete. Custom medical vocabulary names are case sensitive.

    *)
}
type delete_medical_transcription_job_request = {
  1. medical_transcription_job_name : string;
    (*

    The name of the medical transcription job you want to delete. Job names are case sensitive.

    *)
}
type delete_medical_scribe_job_request = {
  1. medical_scribe_job_name : string;
    (*

    The name of the Medical Scribe job you want to delete. Job names are case sensitive.

    *)
}
type delete_language_model_request = {
  1. model_name : string;
    (*

    The name of the custom language model you want to delete. Model names are case sensitive.

    *)
}
type delete_call_analytics_job_response = unit
type delete_call_analytics_job_request = {
  1. call_analytics_job_name : string;
    (*

    The name of the Call Analytics job you want to delete. Job names are case sensitive.

    *)
}
type delete_call_analytics_category_response = unit
type delete_call_analytics_category_request = {
  1. category_name : string;
    (*

    The name of the Call Analytics category you want to delete. Category names are case sensitive.

    *)
}
type create_vocabulary_filter_response = {
  1. last_modified_time : float option;
    (*

    The date and time you created your custom vocabulary filter.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents 12:32 PM UTC-7 on May 4, 2022.

    *)
  2. language_code : language_code option;
    (*

    The language code you selected for your custom vocabulary filter.

    *)
  3. vocabulary_filter_name : string option;
    (*

    The name you chose for your custom vocabulary filter.

    *)
}
type create_vocabulary_filter_request = {
  1. data_access_role_arn : string option;
    (*

    The Amazon Resource Name (ARN) of an IAM role that has permissions to access the Amazon S3 bucket that contains your input files (in this case, your custom vocabulary filter). If the role that you specify doesn’t have the appropriate permissions to access the specified Amazon S3 location, your request fails.

    IAM role ARNs have the format arn:partition:iam::account:role/role-name-with-path. For example: arn:aws:iam::111122223333:role/Admin.

    For more information, see IAM ARNs.

    *)
  2. tags : tag list option;
    (*

    Adds one or more custom tags, each in the form of a key:value pair, to a new custom vocabulary filter at the time you create this new vocabulary filter.

    To learn more about using tags with Amazon Transcribe, refer to Tagging resources.

    *)
  3. vocabulary_filter_file_uri : string option;
    (*

    The Amazon S3 location of the text file that contains your custom vocabulary filter terms. The URI must be located in the same Amazon Web Services Region as the resource you're calling.

    Here's an example URI path: s3://DOC-EXAMPLE-BUCKET/my-vocab-filter-file.txt

    Note that if you include VocabularyFilterFileUri in your request, you cannot use Words; you must choose one or the other.

    *)
  4. words : string list option;
    (*

    Use this parameter if you want to create your custom vocabulary filter by including all desired terms, as comma-separated values, within your request. The other option for creating your vocabulary filter is to save your entries in a text file and upload them to an Amazon S3 bucket, then specify the location of your file using the VocabularyFilterFileUri parameter.

    Note that if you include Words in your request, you cannot use VocabularyFilterFileUri; you must choose one or the other.

    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 to get the character set for your language.

    *)
  5. language_code : language_code;
    (*

    The language code that represents the language of the entries in your vocabulary filter. Each custom vocabulary filter must contain terms in only one language.

    A custom vocabulary filter can only be used to transcribe files in the same language as the filter. For example, if you create a custom vocabulary filter using US English (en-US), you can only apply this filter to files that contain English audio.

    For a list of supported languages and their associated language codes, refer to the Supported languages table.

    *)
  6. vocabulary_filter_name : string;
    (*

    A unique name, chosen by you, for your new custom vocabulary filter.

    This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account. If you try to create a new custom vocabulary filter with the same name as an existing custom vocabulary filter, you get a ConflictException error.

    *)
}
type create_vocabulary_response = {
  1. failure_reason : string option;
    (*

    If VocabularyState is FAILED, FailureReason contains information about why the custom vocabulary request failed. See also: Common Errors.

    *)
  2. last_modified_time : float option;
    (*

    The date and time you created your custom vocabulary.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents 12:32 PM UTC-7 on May 4, 2022.

    *)
  3. vocabulary_state : vocabulary_state option;
    (*

    The processing state of your custom vocabulary. If the state is READY, you can use the custom vocabulary in a StartTranscriptionJob request.

    *)
  4. language_code : language_code option;
    (*

    The language code you selected for your custom vocabulary.

    *)
  5. vocabulary_name : string option;
    (*

    The name you chose for your custom vocabulary.

    *)
}
type create_vocabulary_request = {
  1. data_access_role_arn : string option;
    (*

    The Amazon Resource Name (ARN) of an IAM role that has permissions to access the Amazon S3 bucket that contains your input files (in this case, your custom vocabulary). If the role that you specify doesn’t have the appropriate permissions to access the specified Amazon S3 location, your request fails.

    IAM role ARNs have the format arn:partition:iam::account:role/role-name-with-path. For example: arn:aws:iam::111122223333:role/Admin.

    For more information, see IAM ARNs.

    *)
  2. tags : tag list option;
    (*

    Adds one or more custom tags, each in the form of a key:value pair, to a new custom vocabulary at the time you create this new custom vocabulary.

    To learn more about using tags with Amazon Transcribe, refer to Tagging resources.

    *)
  3. vocabulary_file_uri : string option;
    (*

    The Amazon S3 location of the text file that contains your custom vocabulary. The URI must be located in the same Amazon Web Services Region as the resource you're calling.

    Here's an example URI path: s3://DOC-EXAMPLE-BUCKET/my-vocab-file.txt

    Note that if you include VocabularyFileUri in your request, you cannot use the Phrases flag; you must choose one or the other.

    *)
  4. phrases : string list option;
    (*

    Use this parameter if you want to create your custom vocabulary by including all desired terms, as comma-separated values, within your request. The other option for creating your custom vocabulary is to save your entries in a text file and upload them to an Amazon S3 bucket, then specify the location of your file using the VocabularyFileUri parameter.

    Note that if you include Phrases in your request, you cannot use VocabularyFileUri; you must choose one or the other.

    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 to get the character set for your language.

    *)
  5. language_code : language_code;
    (*

    The language code that represents the language of the entries in your custom vocabulary. Each custom vocabulary must contain terms in only one language.

    A custom vocabulary can only be used to transcribe files in the same language as the custom vocabulary. For example, if you create a custom vocabulary using US English (en-US), you can only apply this custom vocabulary to files that contain English audio.

    For a list of supported languages and their associated language codes, refer to the Supported languages table.

    *)
  6. vocabulary_name : string;
    (*

    A unique name, chosen by you, for your new custom vocabulary.

    This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account. If you try to create a new custom vocabulary with the same name as an existing custom vocabulary, you get a ConflictException error.

    *)
}
type create_medical_vocabulary_response = {
  1. failure_reason : string option;
    (*

    If VocabularyState is FAILED, FailureReason contains information about why the medical transcription job request failed. See also: Common Errors.

    *)
  2. last_modified_time : float option;
    (*

    The date and time you created your custom medical vocabulary.

    Timestamps are in the format YYYY-MM-DD'T'HH:MM:SS.SSSSSS-UTC. For example, 2022-05-04T12:32:58.761000-07:00 represents 12:32 PM UTC-7 on May 4, 2022.

    *)
  3. vocabulary_state : vocabulary_state option;
    (*

    The processing state of your custom medical vocabulary. If the state is READY, you can use the custom vocabulary in a StartMedicalTranscriptionJob request.

    *)
  4. language_code : language_code option;
    (*

    The language code you selected for your custom medical vocabulary. US English (en-US) is the only language supported with Amazon Transcribe Medical.

    *)
  5. vocabulary_name : string option;
    (*

    The name you chose for your custom medical vocabulary.

    *)
}
type create_medical_vocabulary_request = {
  1. tags : tag list option;
    (*

    Adds one or more custom tags, each in the form of a key:value pair, to a new custom medical vocabulary at the time you create this new custom vocabulary.

    To learn more about using tags with Amazon Transcribe, refer to Tagging resources.

    *)
  2. vocabulary_file_uri : string;
    (*

    The Amazon S3 location (URI) of the text file that contains your custom medical vocabulary. The URI must be in the same Amazon Web Services Region as the resource you're calling.

    Here's an example URI path: s3://DOC-EXAMPLE-BUCKET/my-vocab-file.txt

    *)
  3. language_code : language_code;
    (*

    The language code that represents the language of the entries in your custom vocabulary. US English (en-US) is the only language supported with Amazon Transcribe Medical.

    *)
  4. vocabulary_name : string;
    (*

    A unique name, chosen by you, for your new custom medical vocabulary.

    This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account. If you try to create a new custom medical vocabulary with the same name as an existing custom medical vocabulary, you get a ConflictException error.

    *)
}
type create_language_model_response = {
  1. model_status : model_status option;
    (*

    The status of your custom language model. When the status displays as COMPLETED, your model is ready to use.

    *)
  2. input_data_config : input_data_config option;
    (*

    Lists your data access role ARN (Amazon Resource Name) and the Amazon S3 locations you provided for your training (S3Uri) and tuning (TuningDataS3Uri) data.

    *)
  3. model_name : string option;
    (*

    The name of your custom language model.

    *)
  4. base_model_name : base_model_name option;
    (*

    The Amazon Transcribe standard language model, or base model, you specified when creating your custom language model.

    *)
  5. language_code : clm_language_code option;
    (*

    The language code you selected for your custom language model.

    *)
}
type create_language_model_request = {
  1. tags : tag list option;
    (*

    Adds one or more custom tags, each in the form of a key:value pair, to a new custom language model at the time you create this new model.

    To learn more about using tags with Amazon Transcribe, refer to Tagging resources.

    *)
  2. input_data_config : input_data_config;
    (*

    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, which is the Amazon S3 location of your training data, and DataAccessRoleArn, which is the Amazon Resource Name (ARN) of the role that has permission to access your specified Amazon S3 location. You can optionally include TuningDataS3Uri, which is the Amazon S3 location of your tuning data. If you specify different Amazon S3 locations for training and tuning data, the ARN you use must have permissions to access both locations.

    *)
  3. model_name : string;
    (*

    A unique name, chosen by you, for your custom language model.

    This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account. If you try to create a new custom language model with the same name as an existing custom language model, you get a ConflictException error.

    *)
  4. base_model_name : base_model_name;
    (*

    The Amazon Transcribe standard language model, or base model, used to create your custom language model. Amazon Transcribe offers two options for base models: Wideband and Narrowband.

    If the audio you want to transcribe has a sample rate of 16,000 Hz or greater, choose WideBand. To transcribe audio with a sample rate less than 16,000 Hz, choose NarrowBand.

    *)
  5. language_code : clm_language_code;
    (*

    The language code that represents the language of your model. Each custom language model must contain terms in only one language, and the language you select for your custom language model must match the language of your training and tuning data.

    For a list of supported languages and their associated language codes, refer to the Supported languages table. Note that US English (en-US) is the only language supported with Amazon Transcribe Medical.

    A custom language model can only be used to transcribe files in the same language as the model. For example, if you create a custom language model using US English (en-US), you can only apply this model to files that contain English audio.

    *)
}
type create_call_analytics_category_response = {
  1. category_properties : category_properties option;
    (*

    Provides you with the properties of your new category, including its associated rules.

    *)
}
type create_call_analytics_category_request = {
  1. input_type : input_type option;
    (*

    Choose whether you want to create a real-time or a post-call category for your Call Analytics transcription.

    Specifying POST_CALL assigns your category to post-call transcriptions; categories with this input type cannot be applied to streaming (real-time) transcriptions.

    Specifying REAL_TIME assigns your category to streaming transcriptions; categories with this input type cannot be applied to post-call transcriptions.

    If you do not include InputType, your category is created as a post-call category by default.

    *)
  2. rules : rule list;
    (*

    Rules define a Call Analytics category. When creating a new category, you must create between 1 and 20 rules for that category. For each rule, you specify a filter you want applied to the attributes of a call. For example, you can choose a sentiment filter that detects if a customer's sentiment was positive during the last 30 seconds of the call.

    *)
  3. category_name : string;
    (*

    A unique name, chosen by you, for your Call Analytics category. It's helpful to use a detailed naming system that will make sense to you in the future. For example, it's better to use sentiment-positive-last30seconds for a category over a generic name like test-category.

    Category names are case sensitive.

    *)
}

Amazon Transcribe offers three main types of batch transcription: Standard, Medical, and Call Analytics.

type base_document = Smaws_Lib.Json.t

Builders

val make_vocabulary_info : ?vocabulary_state:vocabulary_state -> ?last_modified_time:float -> ?language_code:language_code -> ?vocabulary_name:string -> unit -> vocabulary_info

Create a vocabulary_info type

val make_vocabulary_filter_info : ?last_modified_time:float -> ?language_code:language_code -> ?vocabulary_filter_name:string -> unit -> vocabulary_filter_info

Create a vocabulary_filter_info type

val make_update_vocabulary_response : ?vocabulary_state:vocabulary_state -> ?last_modified_time:float -> ?language_code:language_code -> ?vocabulary_name:string -> unit -> update_vocabulary_response

Create a update_vocabulary_response type

val make_update_vocabulary_request : ?data_access_role_arn:string -> ?vocabulary_file_uri:string -> ?phrases:string list -> language_code:language_code -> vocabulary_name:string -> unit -> update_vocabulary_request

Create a update_vocabulary_request type

val make_update_vocabulary_filter_response : ?last_modified_time:float -> ?language_code:language_code -> ?vocabulary_filter_name:string -> unit -> update_vocabulary_filter_response

Create a update_vocabulary_filter_response type

val make_update_vocabulary_filter_request : ?data_access_role_arn:string -> ?vocabulary_filter_file_uri:string -> ?words:string list -> vocabulary_filter_name:string -> unit -> update_vocabulary_filter_request

Create a update_vocabulary_filter_request type

val make_update_medical_vocabulary_response : ?vocabulary_state:vocabulary_state -> ?last_modified_time:float -> ?language_code:language_code -> ?vocabulary_name:string -> unit -> update_medical_vocabulary_response

Create a update_medical_vocabulary_response type

val make_update_medical_vocabulary_request : vocabulary_file_uri:string -> language_code:language_code -> vocabulary_name:string -> unit -> update_medical_vocabulary_request

Create a update_medical_vocabulary_request type

val make_absolute_time_range : ?last:int -> ?first:int -> ?end_time:int -> ?start_time:int -> unit -> absolute_time_range

Create a absolute_time_range type

val make_relative_time_range : ?last:int -> ?first:int -> ?end_percentage:int -> ?start_percentage:int -> unit -> relative_time_range

Create a relative_time_range type

val make_non_talk_time_filter : ?negate:bool -> ?relative_time_range:relative_time_range -> ?absolute_time_range:absolute_time_range -> ?threshold:int -> unit -> non_talk_time_filter

Create a non_talk_time_filter type

val make_interruption_filter : ?negate:bool -> ?relative_time_range:relative_time_range -> ?absolute_time_range:absolute_time_range -> ?participant_role:participant_role -> ?threshold:int -> unit -> interruption_filter

Create a interruption_filter type

val make_transcript_filter : ?negate:bool -> ?participant_role:participant_role -> ?relative_time_range:relative_time_range -> ?absolute_time_range:absolute_time_range -> targets:string list -> transcript_filter_type:transcript_filter_type -> unit -> transcript_filter

Create a transcript_filter type

val make_sentiment_filter : ?negate:bool -> ?participant_role:participant_role -> ?relative_time_range:relative_time_range -> ?absolute_time_range:absolute_time_range -> sentiments:sentiment_value list -> unit -> sentiment_filter

Create a sentiment_filter type

val make_category_properties : ?input_type:input_type -> ?last_update_time:float -> ?create_time:float -> ?rules:rule list -> ?category_name:string -> unit -> category_properties

Create a category_properties type

val make_update_call_analytics_category_response : ?category_properties:category_properties -> unit -> update_call_analytics_category_response

Create a update_call_analytics_category_response type

val make_update_call_analytics_category_request : ?input_type:input_type -> rules:rule list -> category_name:string -> unit -> update_call_analytics_category_request

Create a update_call_analytics_category_request type

val make_untag_resource_response : unit -> untag_resource_response

Create a untag_resource_response type

val make_untag_resource_request : tag_keys:string list -> resource_arn:string -> unit -> untag_resource_request

Create a untag_resource_request type

val make_content_redaction : ?pii_entity_types:pii_entity_type list -> redaction_output:redaction_output -> redaction_type:redaction_type -> unit -> content_redaction

Create a content_redaction type

val make_model_settings : ?language_model_name:string -> unit -> model_settings

Create a model_settings type

val make_language_code_item : ?duration_in_seconds:float -> ?language_code:language_code -> unit -> language_code_item

Create a language_code_item type

val make_toxicity_detection_settings : toxicity_categories:toxicity_category list -> unit -> toxicity_detection_settings

Create a toxicity_detection_settings type

val make_transcription_job_summary : ?toxicity_detection:toxicity_detection_settings list -> ?language_codes:language_code_item list -> ?identified_language_score:float -> ?identify_multiple_languages:bool -> ?identify_language:bool -> ?model_settings:model_settings -> ?content_redaction:content_redaction -> ?output_location_type:output_location_type -> ?failure_reason:string -> ?transcription_job_status:transcription_job_status -> ?language_code:language_code -> ?completion_time:float -> ?start_time:float -> ?creation_time:float -> ?transcription_job_name:string -> unit -> transcription_job_summary

Create a transcription_job_summary type

val make_media : ?redacted_media_file_uri:string -> ?media_file_uri:string -> unit -> media

Create a media type

val make_transcript : ?redacted_transcript_file_uri:string -> ?transcript_file_uri:string -> unit -> transcript

Create a transcript type

val make_settings : ?vocabulary_filter_method:vocabulary_filter_method -> ?vocabulary_filter_name:string -> ?max_alternatives:int -> ?show_alternatives:bool -> ?channel_identification:bool -> ?max_speaker_labels:int -> ?show_speaker_labels:bool -> ?vocabulary_name:string -> unit -> settings

Create a settings type

val make_job_execution_settings : ?data_access_role_arn:string -> ?allow_deferred_execution:bool -> unit -> job_execution_settings

Create a job_execution_settings type

val make_tag : value:string -> key:string -> unit -> tag

Create a tag type

val make_subtitles_output : ?output_start_index:int -> ?subtitle_file_uris:string list -> ?formats:subtitle_format list -> unit -> subtitles_output

Create a subtitles_output type

val make_language_id_settings : ?language_model_name:string -> ?vocabulary_filter_name:string -> ?vocabulary_name:string -> unit -> language_id_settings

Create a language_id_settings type

val make_transcription_job : ?toxicity_detection:toxicity_detection_settings list -> ?language_id_settings:(string * language_id_settings) list -> ?subtitles:subtitles_output -> ?tags:tag list -> ?language_codes:language_code_item list -> ?identified_language_score:float -> ?language_options:language_code list -> ?identify_multiple_languages:bool -> ?identify_language:bool -> ?content_redaction:content_redaction -> ?job_execution_settings:job_execution_settings -> ?model_settings:model_settings -> ?settings:settings -> ?failure_reason:string -> ?completion_time:float -> ?creation_time:float -> ?start_time:float -> ?transcript:transcript -> ?media:media -> ?media_format:media_format -> ?media_sample_rate_hertz:int -> ?language_code:language_code -> ?transcription_job_status:transcription_job_status -> ?transcription_job_name:string -> unit -> transcription_job

Create a transcription_job type

val make_tag_resource_response : unit -> tag_resource_response

Create a tag_resource_response type

val make_tag_resource_request : tags:tag list -> resource_arn:string -> unit -> tag_resource_request

Create a tag_resource_request type

val make_start_transcription_job_response : ?transcription_job:transcription_job -> unit -> start_transcription_job_response

Create a start_transcription_job_response type

val make_subtitles : ?output_start_index:int -> ?formats:subtitle_format list -> unit -> subtitles

Create a subtitles type

val make_start_transcription_job_request : ?toxicity_detection:toxicity_detection_settings list -> ?language_id_settings:(string * language_id_settings) list -> ?tags:tag list -> ?subtitles:subtitles -> ?language_options:language_code list -> ?identify_multiple_languages:bool -> ?identify_language:bool -> ?content_redaction:content_redaction -> ?job_execution_settings:job_execution_settings -> ?model_settings:model_settings -> ?settings:settings -> ?kms_encryption_context:(string * string) list -> ?output_encryption_kms_key_id:string -> ?output_key:string -> ?output_bucket_name:string -> ?media_format:media_format -> ?media_sample_rate_hertz:int -> ?language_code:language_code -> media:media -> transcription_job_name:string -> unit -> start_transcription_job_request

Create a start_transcription_job_request type

val make_medical_transcript : ?transcript_file_uri:string -> unit -> medical_transcript

Create a medical_transcript type

val make_medical_transcription_setting : ?vocabulary_name:string -> ?max_alternatives:int -> ?show_alternatives:bool -> ?channel_identification:bool -> ?max_speaker_labels:int -> ?show_speaker_labels:bool -> unit -> medical_transcription_setting

Create a medical_transcription_setting type

val make_medical_transcription_job : ?tags:tag list -> ?type_:type_ -> ?specialty:specialty -> ?content_identification_type:medical_content_identification_type -> ?settings:medical_transcription_setting -> ?failure_reason:string -> ?completion_time:float -> ?creation_time:float -> ?start_time:float -> ?transcript:medical_transcript -> ?media:media -> ?media_format:media_format -> ?media_sample_rate_hertz:int -> ?language_code:language_code -> ?transcription_job_status:transcription_job_status -> ?medical_transcription_job_name:string -> unit -> medical_transcription_job

Create a medical_transcription_job type

val make_start_medical_transcription_job_response : ?medical_transcription_job:medical_transcription_job -> unit -> start_medical_transcription_job_response

Create a start_medical_transcription_job_response type

val make_start_medical_transcription_job_request : ?tags:tag list -> ?content_identification_type:medical_content_identification_type -> ?settings:medical_transcription_setting -> ?kms_encryption_context:(string * string) list -> ?output_encryption_kms_key_id:string -> ?output_key:string -> ?media_format:media_format -> ?media_sample_rate_hertz:int -> type_:type_ -> specialty:specialty -> output_bucket_name:string -> media:media -> language_code:language_code -> medical_transcription_job_name:string -> unit -> start_medical_transcription_job_request

Create a start_medical_transcription_job_request type

val make_medical_scribe_output : clinical_document_uri:string -> transcript_file_uri:string -> unit -> medical_scribe_output

Create a medical_scribe_output type

val make_medical_scribe_settings : ?vocabulary_filter_method:vocabulary_filter_method -> ?vocabulary_filter_name:string -> ?vocabulary_name:string -> ?channel_identification:bool -> ?max_speaker_labels:int -> ?show_speaker_labels:bool -> unit -> medical_scribe_settings

Create a medical_scribe_settings type

val make_medical_scribe_channel_definition : participant_role:medical_scribe_participant_role -> channel_id:int -> unit -> medical_scribe_channel_definition

Create a medical_scribe_channel_definition type

val make_medical_scribe_job : ?tags:tag list -> ?channel_definitions:medical_scribe_channel_definition list -> ?data_access_role_arn:string -> ?settings:medical_scribe_settings -> ?failure_reason:string -> ?completion_time:float -> ?creation_time:float -> ?start_time:float -> ?medical_scribe_output:medical_scribe_output -> ?media:media -> ?language_code:medical_scribe_language_code -> ?medical_scribe_job_status:medical_scribe_job_status -> ?medical_scribe_job_name:string -> unit -> medical_scribe_job

Create a medical_scribe_job type

val make_start_medical_scribe_job_response : ?medical_scribe_job:medical_scribe_job -> unit -> start_medical_scribe_job_response

Create a start_medical_scribe_job_response type

val make_start_medical_scribe_job_request : ?tags:tag list -> ?channel_definitions:medical_scribe_channel_definition list -> ?kms_encryption_context:(string * string) list -> ?output_encryption_kms_key_id:string -> settings:medical_scribe_settings -> data_access_role_arn:string -> output_bucket_name:string -> media:media -> medical_scribe_job_name:string -> unit -> start_medical_scribe_job_request

Create a start_medical_scribe_job_request type

val make_call_analytics_skipped_feature : ?message:string -> ?reason_code:call_analytics_skipped_reason_code -> ?feature:call_analytics_feature -> unit -> call_analytics_skipped_feature

Create a call_analytics_skipped_feature type

val make_call_analytics_job_details : ?skipped:call_analytics_skipped_feature list -> unit -> call_analytics_job_details

Create a call_analytics_job_details type

val make_summarization : generate_abstractive_summary:bool -> unit -> summarization

Create a summarization type

val make_call_analytics_job_settings : ?summarization:summarization -> ?language_id_settings:(string * language_id_settings) list -> ?language_options:language_code list -> ?content_redaction:content_redaction -> ?language_model_name:string -> ?vocabulary_filter_method:vocabulary_filter_method -> ?vocabulary_filter_name:string -> ?vocabulary_name:string -> unit -> call_analytics_job_settings

Create a call_analytics_job_settings type

val make_channel_definition : ?participant_role:participant_role -> ?channel_id:int -> unit -> channel_definition

Create a channel_definition type

val make_call_analytics_job : ?channel_definitions:channel_definition list -> ?settings:call_analytics_job_settings -> ?identified_language_score:float -> ?data_access_role_arn:string -> ?failure_reason:string -> ?completion_time:float -> ?creation_time:float -> ?start_time:float -> ?transcript:transcript -> ?media:media -> ?media_format:media_format -> ?media_sample_rate_hertz:int -> ?language_code:language_code -> ?call_analytics_job_details:call_analytics_job_details -> ?call_analytics_job_status:call_analytics_job_status -> ?call_analytics_job_name:string -> unit -> call_analytics_job

Create a call_analytics_job type

val make_start_call_analytics_job_response : ?call_analytics_job:call_analytics_job -> unit -> start_call_analytics_job_response

Create a start_call_analytics_job_response type

val make_start_call_analytics_job_request : ?channel_definitions:channel_definition list -> ?settings:call_analytics_job_settings -> ?data_access_role_arn:string -> ?output_encryption_kms_key_id:string -> ?output_location:string -> media:media -> call_analytics_job_name:string -> unit -> start_call_analytics_job_request

Create a start_call_analytics_job_request type

val make_list_vocabulary_filters_response : ?vocabulary_filters:vocabulary_filter_info list -> ?next_token:string -> unit -> list_vocabulary_filters_response

Create a list_vocabulary_filters_response type

val make_list_vocabulary_filters_request : ?name_contains:string -> ?max_results:int -> ?next_token:string -> unit -> list_vocabulary_filters_request

Create a list_vocabulary_filters_request type

val make_list_vocabularies_response : ?vocabularies:vocabulary_info list -> ?next_token:string -> ?status:vocabulary_state -> unit -> list_vocabularies_response

Create a list_vocabularies_response type

val make_list_vocabularies_request : ?name_contains:string -> ?state_equals:vocabulary_state -> ?max_results:int -> ?next_token:string -> unit -> list_vocabularies_request

Create a list_vocabularies_request type

val make_list_transcription_jobs_response : ?transcription_job_summaries:transcription_job_summary list -> ?next_token:string -> ?status:transcription_job_status -> unit -> list_transcription_jobs_response

Create a list_transcription_jobs_response type

val make_list_transcription_jobs_request : ?max_results:int -> ?next_token:string -> ?job_name_contains:string -> ?status:transcription_job_status -> unit -> list_transcription_jobs_request

Create a list_transcription_jobs_request type

val make_list_tags_for_resource_response : ?tags:tag list -> ?resource_arn:string -> unit -> list_tags_for_resource_response

Create a list_tags_for_resource_response type

val make_list_tags_for_resource_request : resource_arn:string -> unit -> list_tags_for_resource_request

Create a list_tags_for_resource_request type

val make_list_medical_vocabularies_response : ?vocabularies:vocabulary_info list -> ?next_token:string -> ?status:vocabulary_state -> unit -> list_medical_vocabularies_response

Create a list_medical_vocabularies_response type

val make_list_medical_vocabularies_request : ?name_contains:string -> ?state_equals:vocabulary_state -> ?max_results:int -> ?next_token:string -> unit -> list_medical_vocabularies_request

Create a list_medical_vocabularies_request type

val make_medical_transcription_job_summary : ?type_:type_ -> ?content_identification_type:medical_content_identification_type -> ?specialty:specialty -> ?output_location_type:output_location_type -> ?failure_reason:string -> ?transcription_job_status:transcription_job_status -> ?language_code:language_code -> ?completion_time:float -> ?start_time:float -> ?creation_time:float -> ?medical_transcription_job_name:string -> unit -> medical_transcription_job_summary

Create a medical_transcription_job_summary type

val make_list_medical_transcription_jobs_response : ?medical_transcription_job_summaries:medical_transcription_job_summary list -> ?next_token:string -> ?status:transcription_job_status -> unit -> list_medical_transcription_jobs_response

Create a list_medical_transcription_jobs_response type

val make_list_medical_transcription_jobs_request : ?max_results:int -> ?next_token:string -> ?job_name_contains:string -> ?status:transcription_job_status -> unit -> list_medical_transcription_jobs_request

Create a list_medical_transcription_jobs_request type

val make_medical_scribe_job_summary : ?failure_reason:string -> ?medical_scribe_job_status:medical_scribe_job_status -> ?language_code:medical_scribe_language_code -> ?completion_time:float -> ?start_time:float -> ?creation_time:float -> ?medical_scribe_job_name:string -> unit -> medical_scribe_job_summary

Create a medical_scribe_job_summary type

val make_list_medical_scribe_jobs_response : ?medical_scribe_job_summaries:medical_scribe_job_summary list -> ?next_token:string -> ?status:medical_scribe_job_status -> unit -> list_medical_scribe_jobs_response

Create a list_medical_scribe_jobs_response type

val make_list_medical_scribe_jobs_request : ?max_results:int -> ?next_token:string -> ?job_name_contains:string -> ?status:medical_scribe_job_status -> unit -> list_medical_scribe_jobs_request

Create a list_medical_scribe_jobs_request type

val make_input_data_config : ?tuning_data_s3_uri:string -> data_access_role_arn:string -> s3_uri:string -> unit -> input_data_config

Create a input_data_config type

val make_language_model : ?input_data_config:input_data_config -> ?failure_reason:string -> ?upgrade_availability:bool -> ?model_status:model_status -> ?base_model_name:base_model_name -> ?language_code:clm_language_code -> ?last_modified_time:float -> ?create_time:float -> ?model_name:string -> unit -> language_model

Create a language_model type

val make_list_language_models_response : ?models:language_model list -> ?next_token:string -> unit -> list_language_models_response

Create a list_language_models_response type

val make_list_language_models_request : ?max_results:int -> ?next_token:string -> ?name_contains:string -> ?status_equals:model_status -> unit -> list_language_models_request

Create a list_language_models_request type

val make_call_analytics_job_summary : ?failure_reason:string -> ?call_analytics_job_details:call_analytics_job_details -> ?call_analytics_job_status:call_analytics_job_status -> ?language_code:language_code -> ?completion_time:float -> ?start_time:float -> ?creation_time:float -> ?call_analytics_job_name:string -> unit -> call_analytics_job_summary

Create a call_analytics_job_summary type

val make_list_call_analytics_jobs_response : ?call_analytics_job_summaries:call_analytics_job_summary list -> ?next_token:string -> ?status:call_analytics_job_status -> unit -> list_call_analytics_jobs_response

Create a list_call_analytics_jobs_response type

val make_list_call_analytics_jobs_request : ?max_results:int -> ?next_token:string -> ?job_name_contains:string -> ?status:call_analytics_job_status -> unit -> list_call_analytics_jobs_request

Create a list_call_analytics_jobs_request type

val make_list_call_analytics_categories_response : ?categories:category_properties list -> ?next_token:string -> unit -> list_call_analytics_categories_response

Create a list_call_analytics_categories_response type

val make_list_call_analytics_categories_request : ?max_results:int -> ?next_token:string -> unit -> list_call_analytics_categories_request

Create a list_call_analytics_categories_request type

val make_get_vocabulary_filter_response : ?download_uri:string -> ?last_modified_time:float -> ?language_code:language_code -> ?vocabulary_filter_name:string -> unit -> get_vocabulary_filter_response

Create a get_vocabulary_filter_response type

val make_get_vocabulary_filter_request : vocabulary_filter_name:string -> unit -> get_vocabulary_filter_request

Create a get_vocabulary_filter_request type

val make_get_vocabulary_response : ?download_uri:string -> ?failure_reason:string -> ?last_modified_time:float -> ?vocabulary_state:vocabulary_state -> ?language_code:language_code -> ?vocabulary_name:string -> unit -> get_vocabulary_response

Create a get_vocabulary_response type

val make_get_vocabulary_request : vocabulary_name:string -> unit -> get_vocabulary_request

Create a get_vocabulary_request type

val make_get_transcription_job_response : ?transcription_job:transcription_job -> unit -> get_transcription_job_response

Create a get_transcription_job_response type

val make_get_transcription_job_request : transcription_job_name:string -> unit -> get_transcription_job_request

Create a get_transcription_job_request type

val make_get_medical_vocabulary_response : ?download_uri:string -> ?failure_reason:string -> ?last_modified_time:float -> ?vocabulary_state:vocabulary_state -> ?language_code:language_code -> ?vocabulary_name:string -> unit -> get_medical_vocabulary_response

Create a get_medical_vocabulary_response type

val make_get_medical_vocabulary_request : vocabulary_name:string -> unit -> get_medical_vocabulary_request

Create a get_medical_vocabulary_request type

val make_get_medical_transcription_job_response : ?medical_transcription_job:medical_transcription_job -> unit -> get_medical_transcription_job_response

Create a get_medical_transcription_job_response type

val make_get_medical_transcription_job_request : medical_transcription_job_name:string -> unit -> get_medical_transcription_job_request

Create a get_medical_transcription_job_request type

val make_get_medical_scribe_job_response : ?medical_scribe_job:medical_scribe_job -> unit -> get_medical_scribe_job_response

Create a get_medical_scribe_job_response type

val make_get_medical_scribe_job_request : medical_scribe_job_name:string -> unit -> get_medical_scribe_job_request

Create a get_medical_scribe_job_request type

val make_get_call_analytics_job_response : ?call_analytics_job:call_analytics_job -> unit -> get_call_analytics_job_response

Create a get_call_analytics_job_response type

val make_get_call_analytics_job_request : call_analytics_job_name:string -> unit -> get_call_analytics_job_request

Create a get_call_analytics_job_request type

val make_get_call_analytics_category_response : ?category_properties:category_properties -> unit -> get_call_analytics_category_response

Create a get_call_analytics_category_response type

val make_get_call_analytics_category_request : category_name:string -> unit -> get_call_analytics_category_request

Create a get_call_analytics_category_request type

val make_describe_language_model_response : ?language_model:language_model -> unit -> describe_language_model_response

Create a describe_language_model_response type

val make_describe_language_model_request : model_name:string -> unit -> describe_language_model_request

Create a describe_language_model_request type

val make_delete_vocabulary_filter_request : vocabulary_filter_name:string -> unit -> delete_vocabulary_filter_request

Create a delete_vocabulary_filter_request type

val make_delete_vocabulary_request : vocabulary_name:string -> unit -> delete_vocabulary_request

Create a delete_vocabulary_request type

val make_delete_transcription_job_request : transcription_job_name:string -> unit -> delete_transcription_job_request

Create a delete_transcription_job_request type

val make_delete_medical_vocabulary_request : vocabulary_name:string -> unit -> delete_medical_vocabulary_request

Create a delete_medical_vocabulary_request type

val make_delete_medical_transcription_job_request : medical_transcription_job_name:string -> unit -> delete_medical_transcription_job_request

Create a delete_medical_transcription_job_request type

val make_delete_medical_scribe_job_request : medical_scribe_job_name:string -> unit -> delete_medical_scribe_job_request

Create a delete_medical_scribe_job_request type

val make_delete_language_model_request : model_name:string -> unit -> delete_language_model_request

Create a delete_language_model_request type

val make_delete_call_analytics_job_response : unit -> delete_call_analytics_job_response

Create a delete_call_analytics_job_response type

val make_delete_call_analytics_job_request : call_analytics_job_name:string -> unit -> delete_call_analytics_job_request

Create a delete_call_analytics_job_request type

val make_delete_call_analytics_category_response : unit -> delete_call_analytics_category_response

Create a delete_call_analytics_category_response type

val make_delete_call_analytics_category_request : category_name:string -> unit -> delete_call_analytics_category_request

Create a delete_call_analytics_category_request type

val make_create_vocabulary_filter_response : ?last_modified_time:float -> ?language_code:language_code -> ?vocabulary_filter_name:string -> unit -> create_vocabulary_filter_response

Create a create_vocabulary_filter_response type

val make_create_vocabulary_filter_request : ?data_access_role_arn:string -> ?tags:tag list -> ?vocabulary_filter_file_uri:string -> ?words:string list -> language_code:language_code -> vocabulary_filter_name:string -> unit -> create_vocabulary_filter_request

Create a create_vocabulary_filter_request type

val make_create_vocabulary_response : ?failure_reason:string -> ?last_modified_time:float -> ?vocabulary_state:vocabulary_state -> ?language_code:language_code -> ?vocabulary_name:string -> unit -> create_vocabulary_response

Create a create_vocabulary_response type

val make_create_vocabulary_request : ?data_access_role_arn:string -> ?tags:tag list -> ?vocabulary_file_uri:string -> ?phrases:string list -> language_code:language_code -> vocabulary_name:string -> unit -> create_vocabulary_request

Create a create_vocabulary_request type

val make_create_medical_vocabulary_response : ?failure_reason:string -> ?last_modified_time:float -> ?vocabulary_state:vocabulary_state -> ?language_code:language_code -> ?vocabulary_name:string -> unit -> create_medical_vocabulary_response

Create a create_medical_vocabulary_response type

val make_create_medical_vocabulary_request : ?tags:tag list -> vocabulary_file_uri:string -> language_code:language_code -> vocabulary_name:string -> unit -> create_medical_vocabulary_request

Create a create_medical_vocabulary_request type

val make_create_language_model_response : ?model_status:model_status -> ?input_data_config:input_data_config -> ?model_name:string -> ?base_model_name:base_model_name -> ?language_code:clm_language_code -> unit -> create_language_model_response

Create a create_language_model_response type

val make_create_language_model_request : ?tags:tag list -> input_data_config:input_data_config -> model_name:string -> base_model_name:base_model_name -> language_code:clm_language_code -> unit -> create_language_model_request

Create a create_language_model_request type

val make_create_call_analytics_category_response : ?category_properties:category_properties -> unit -> create_call_analytics_category_response

Create a create_call_analytics_category_response type

val make_create_call_analytics_category_request : ?input_type:input_type -> rules:rule list -> category_name:string -> unit -> create_call_analytics_category_request

Create a create_call_analytics_category_request type

Operations

module CreateCallAnalyticsCategory : sig ... end
module CreateLanguageModel : sig ... end
module CreateMedicalVocabulary : sig ... end
module CreateVocabulary : sig ... end
module CreateVocabularyFilter : sig ... end
module DeleteCallAnalyticsCategory : sig ... end
module DeleteCallAnalyticsJob : sig ... end
module DeleteLanguageModel : sig ... end
module DeleteMedicalScribeJob : sig ... end
module DeleteMedicalTranscriptionJob : sig ... end
module DeleteMedicalVocabulary : sig ... end
module DeleteTranscriptionJob : sig ... end
module DeleteVocabulary : sig ... end
module DeleteVocabularyFilter : sig ... end
module DescribeLanguageModel : sig ... end
module GetCallAnalyticsCategory : sig ... end
module GetCallAnalyticsJob : sig ... end
module GetMedicalScribeJob : sig ... end
module GetMedicalTranscriptionJob : sig ... end
module GetMedicalVocabulary : sig ... end
module GetTranscriptionJob : sig ... end
module GetVocabulary : sig ... end
module GetVocabularyFilter : sig ... end
module ListCallAnalyticsCategories : sig ... end
module ListCallAnalyticsJobs : sig ... end
module ListLanguageModels : sig ... end
module ListMedicalScribeJobs : sig ... end
module ListMedicalTranscriptionJobs : sig ... end
module ListMedicalVocabularies : sig ... end
module ListTagsForResource : sig ... end
module ListTranscriptionJobs : sig ... end
module ListVocabularies : sig ... end
module ListVocabularyFilters : sig ... end
module StartCallAnalyticsJob : sig ... end
module StartMedicalScribeJob : sig ... end
module StartMedicalTranscriptionJob : sig ... end
module StartTranscriptionJob : sig ... end
module TagResource : sig ... end
module UntagResource : sig ... end
module UpdateCallAnalyticsCategory : sig ... end
module UpdateMedicalVocabulary : sig ... end
module UpdateVocabulary : sig ... end
module UpdateVocabularyFilter : sig ... end