Hume AI subpackage_batch API

openapi: 3.2.0
info:
  title: Expression Measurement Subpackage Batch API
  version: 1.0.0
servers:
- url: https://api.hume.ai
tags:
- name: subpackage_batch
paths:
  /v0/batch/jobs:
    get:
      operationId: list-jobs
      summary: List jobs
      description: Sort and filter jobs.
      tags:
      - subpackage_batch
      parameters:
      - name: limit
        in: query
        description: The maximum number of jobs to include in the response.
        required: false
        schema:
          type: integer
          default: 50
      - name: status
        in: query
        description: "Include only jobs of this status in the response. There are four possible statuses:\n\n- `QUEUED`: The job has been received and is waiting to be processed.\n\n- `IN_PROGRESS`: The job is currently being processed. \n\n- `COMPLETED`: The job has finished processing.\n\n- `FAILED`: The job encountered an error and could not be completed successfully."
        required: false
        schema:
          type: array
          items:
            $ref: '#/components/schemas/batch_Status'
      - name: when
        in: query
        description: Specify whether to include jobs created before or after a given `timestamp_ms`.
        required: false
        schema:
          $ref: '#/components/schemas/batch_V0BatchJobsGetParametersWhen'
      - name: timestamp_ms
        in: query
        description: "Provide a timestamp in milliseconds to filter jobs.\n\n When combined with the `when` parameter, you can filter jobs before or after the given timestamp. Defaults to the current Unix timestamp if one is not provided."
        required: false
        schema:
          type: integer
          format: int64
          default: 1704319392247
      - name: sort_by
        in: query
        description: 'Specify which timestamp to sort the jobs by.


          - `created`: Sort jobs by the time of creation, indicated by `created_timestamp_ms`.


          - `started`: Sort jobs by the time processing started, indicated by `started_timestamp_ms`.


          - `ended`: Sort jobs by the time processing ended, indicated by `ended_timestamp_ms`.'
        required: false
        schema:
          $ref: '#/components/schemas/batch_V0BatchJobsGetParametersSortBy'
      - name: direction
        in: query
        description: 'Specify the order in which to sort the jobs. Defaults to descending order.


          - `asc`: Sort in ascending order (chronological, with the oldest records first).


          - `desc`: Sort in descending order (reverse-chronological, with the newest records first).'
        required: false
        schema:
          $ref: '#/components/schemas/batch_V0BatchJobsGetParametersDirection'
      - name: X-Hume-Api-Key
        in: header
        required: true
        schema:
          type: string
      responses:
        '200':
          description: ''
          content:
            application/json:
              schema:
                type: array
                items:
                  $ref: '#/components/schemas/batch_UnionJob'
    post:
      operationId: start-inference-job-from-local-file
      summary: Start inference job from local file
      description: Start a new batch inference job.
      tags:
      - subpackage_batch
      responses:
        '200':
          description: ''
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/batch_JobId'
      requestBody:
        content:
          multipart/form-data:
            schema:
              type: object
              properties:
                json:
                  $ref: '#/components/schemas/batch_V0BatchJobsPostRequestBodyContentMultipartFormDataSchemaJson'
                  description: Stringified JSON object containing the inference job configuration.
                file:
                  type: array
                  items:
                    type: string
                    format: binary
                  description: 'Local media files (see recommended input filetypes) to be processed.


                    If you wish to supply more than 100 files, consider providing them as an archive (`.zip`, `.tar.gz`, `.tar.bz2`, `.tar.xz`).'
              required:
              - file
  /v0/batch/jobs/{id}:
    get:
      operationId: get-job-details
      summary: Get job details
      description: Get the request details and state of a given job.
      tags:
      - subpackage_batch
      parameters:
      - name: id
        in: path
        description: The unique identifier for the job.
        required: true
        schema:
          type: string
          format: uuid
      - name: X-Hume-Api-Key
        in: header
        required: true
        schema:
          type: string
      responses:
        '200':
          description: ''
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/batch_UnionJob'
  /v0/batch/jobs/{id}/predictions:
    get:
      operationId: get-job-predictions
      summary: Get job predictions
      description: Get the JSON predictions of a completed inference job.
      tags:
      - subpackage_batch
      parameters:
      - name: id
        in: path
        description: The unique identifier for the job.
        required: true
        schema:
          type: string
          format: uuid
      - name: X-Hume-Api-Key
        in: header
        required: true
        schema:
          type: string
      responses:
        '200':
          description: ''
          content:
            application/json:
              schema:
                type: array
                items:
                  $ref: '#/components/schemas/batch_UnionPredictResult'
  /v0/batch/jobs/{id}/artifacts:
    get:
      operationId: get-job-artifacts
      summary: Get job artifacts
      description: Get the artifacts ZIP of a completed inference job.
      tags:
      - subpackage_batch
      parameters:
      - name: id
        in: path
        description: The unique identifier for the job.
        required: true
        schema:
          type: string
          format: uuid
      - name: X-Hume-Api-Key
        in: header
        required: true
        schema:
          type: string
      responses:
        '200':
          description: ''
          content:
            application/octet-stream:
              schema:
                type: string
                format: binary
components:
  schemas:
    batch_UnionJob_Job_Inference:
      type: object
      properties:
        job_id:
          type: string
          format: uuid
          description: The ID associated with this job.
        request:
          $ref: '#/components/schemas/batch_InferenceRequest'
          description: The request that initiated the job.
        state:
          $ref: '#/components/schemas/batch_State_Inference'
          description: The current state of the job.
        type:
          type: string
          description: 'Denotes the job type.


            Jobs created with the Expression Measurement API will have this field set to `INFERENCE`.'
      required:
      - job_id
      - request
      - state
      - type
      title: UnionJob_Job<Inference>
    batch_LanguageSentiment:
      type: object
      properties: {}
      title: LanguageSentiment
    batch_Source:
      oneOf:
      - type: object
        properties:
          type:
            type: string
          url:
            type: string
            description: The URL of the source media file.
        required:
        - type
        - url
        description: url variant
      - type: object
        properties:
          type:
            type: string
          filename:
            type: string
            description: The name of the file.
          content_type:
            type: string
            description: The content type of the file.
          md5sum:
            type: string
            description: The MD5 checksum of the file.
        required:
        - type
        - md5sum
        description: file variant
      - type: object
        properties:
          type:
            type: string
        required:
        - type
        description: text variant
      discriminator:
        propertyName: type
      title: Source
    batch_FacePrediction:
      type: object
      properties:
        frame:
          type: integer
          format: uint64
          description: Frame number
        time:
          type: number
          format: double
          description: Time in seconds when face detection occurred.
        prob:
          type: number
          format: double
          description: The predicted probability that a detected face was actually a face.
        box:
          $ref: '#/components/schemas/batch_BoundingBox'
        emotions:
          type: array
          items:
            $ref: '#/components/schemas/batch_EmotionScore'
          description: A high-dimensional embedding in emotion space.
        facs:
          type: array
          items:
            $ref: '#/components/schemas/batch_FacsScore'
          description: FACS 2.0 features and their scores.
        descriptions:
          type: array
          items:
            $ref: '#/components/schemas/batch_DescriptionsScore'
          description: Modality-specific descriptive features and their scores.
      required:
      - frame
      - time
      - prob
      - box
      - emotions
      title: FacePrediction
    batch_ToxicityScore:
      type: object
      properties:
        name:
          type: string
          description: Category of toxicity.
        score:
          type: number
          format: double
          description: Prediction for this category of toxicity
      required:
      - name
      - score
      title: ToxicityScore
    batch_ProsodyGranularity:
      type: object
      properties: {}
      title: ProsodyGranularity
    batch_GroupedPredictions_FacePrediction:
      type: object
      properties:
        id:
          type: string
          description: An automatically generated label to identify individuals in your media file. Will be `unknown` if you have chosen to disable identification, or if the model is unable to distinguish between individuals.
        predictions:
          type: array
          items:
            $ref: '#/components/schemas/batch_FacePrediction'
      required:
      - id
      - predictions
      title: GroupedPredictions<FacePrediction>
    batch_State_Inference:
      oneOf:
      - type: object
        properties:
          status:
            type: string
          created_timestamp_ms:
            type: integer
            format: int64
            description: When this job was created (Unix timestamp in milliseconds).
        required:
        - status
        - created_timestamp_ms
        description: QUEUED variant
      - type: object
        properties:
          status:
            type: string
          created_timestamp_ms:
            type: integer
            format: int64
            description: When this job was created (Unix timestamp in milliseconds).
          started_timestamp_ms:
            type: integer
            format: int64
            description: When this job started (Unix timestamp in milliseconds).
        required:
        - status
        - created_timestamp_ms
        - started_timestamp_ms
        description: IN_PROGRESS variant
      - type: object
        properties:
          status:
            type: string
          created_timestamp_ms:
            type: integer
            format: int64
            description: When this job was created (Unix timestamp in milliseconds).
          started_timestamp_ms:
            type: integer
            format: int64
            description: When this job started (Unix timestamp in milliseconds).
          ended_timestamp_ms:
            type: integer
            format: int64
            description: When this job ended (Unix timestamp in milliseconds).
          num_predictions:
            type: integer
            format: uint64
            description: The number of predictions that were generated by this job.
          num_errors:
            type: integer
            format: uint64
            description: The number of errors that occurred while running this job.
        required:
        - status
        - created_timestamp_ms
        - started_timestamp_ms
        - ended_timestamp_ms
        - num_predictions
        - num_errors
        description: COMPLETED variant
      - type: object
        properties:
          status:
            type: string
          created_timestamp_ms:
            type: integer
            format: int64
            description: When this job was created (Unix timestamp in milliseconds).
          started_timestamp_ms:
            type: integer
            format: int64
            description: When this job started (Unix timestamp in milliseconds).
          ended_timestamp_ms:
            type: integer
            format: int64
            description: When this job ended (Unix timestamp in milliseconds).
          message:
            type: string
            description: An error message.
        required:
        - status
        - created_timestamp_ms
        - started_timestamp_ms
        - ended_timestamp_ms
        - message
        description: FAILED variant
      discriminator:
        propertyName: status
      title: State<Inference>
    batch_FaceFacs:
      type: object
      properties: {}
      title: FaceFacs
    batch_ModelsLanguage:
      type: object
      properties:
        granularity:
          $ref: '#/components/schemas/batch_LanguageGranularity'
        sentiment:
          $ref: '#/components/schemas/batch_LanguageSentiment'
        toxicity:
          $ref: '#/components/schemas/batch_LanguageToxicity'
        identify_speakers:
          type: boolean
          default: false
          description: Whether to return identifiers for speakers over time. If `true`, unique identifiers will be assigned to spoken words to differentiate different speakers. If `false`, all speakers will be tagged with an `unknown` ID.
      title: ModelsLanguage
    batch_GroupedPredictions_NerPrediction:
      type: object
      properties:
        id:
          type: string
          description: An automatically generated label to identify individuals in your media file. Will be `unknown` if you have chosen to disable identification, or if the model is unable to distinguish between individuals.
        predictions:
          type: array
          items:
            $ref: '#/components/schemas/batch_NerPrediction'
      required:
      - id
      - predictions
      title: GroupedPredictions<NerPrediction>
    batch_Null:
      type: object
      properties: {}
      description: No associated metadata for this model. Value will be `null`.
      title: 'Null'
    batch_InferenceRequestTranscription:
      type: object
      properties:
        language:
          $ref: '#/components/schemas/batch_TranscriptionLanguage'
          description: 'By default, we use an automated language detection method for our Speech Prosody, Language, and NER models. However, if you know what language is being spoken in your media samples, you can specify it via its BCP-47 tag and potentially obtain more accurate results.


            You can specify any of the following languages:

            - Chinese: `zh`

            - Danish: `da`

            - Dutch: `nl`

            - English: `en`

            - English (Australia): `en-AU`

            - English (India): `en-IN`

            - English (New Zealand): `en-NZ`

            - English (United Kingdom): `en-GB`

            - French: `fr`

            - French (Canada): `fr-CA`

            - German: `de`

            - Hindi: `hi`

            - Hindi (Roman Script): `hi-Latn`

            - Indonesian: `id`

            - Italian: `it`

            - Japanese: `ja`

            - Korean: `ko`

            - Norwegian: `no`

            - Polish: `pl`

            - Portuguese: `pt`

            - Portuguese (Brazil): `pt-BR`

            - Portuguese (Portugal): `pt-PT`

            - Russian: `ru`

            - Spanish: `es`

            - Spanish (Latin America): `es-419`

            - Swedish: `sv`

            - Tamil: `ta`

            - Turkish: `tr`

            - Ukrainian: `uk`'
        identify_speakers:
          type: boolean
          default: false
          description: Whether to return identifiers for speakers over time. If `true`, unique identifiers will be assigned to spoken words to differentiate different speakers. If `false`, all speakers will be tagged with an `unknown` ID.
        confidence_threshold:
          type: number
          format: double
          default: 0.5
          description: Transcript confidence threshold. Transcripts generated with a confidence less than this threshold will be considered invalid and not used as an input for model inference.
      title: InferenceRequestTranscription
    batch_File:
      type: object
      properties:
        filename:
          type: string
          description: The name of the file.
        content_type:
          type: string
          description: The content type of the file.
        md5sum:
          type: string
          description: The MD5 checksum of the file.
      required:
      - md5sum
      description: The list of files submitted for analysis.
      title: File
    batch_GroupedPredictions_ProsodyPrediction:
      type: object
      properties:
        id:
          type: string
          description: An automatically generated label to identify individuals in your media file. Will be `unknown` if you have chosen to disable identification, or if the model is unable to distinguish between individuals.
        predictions:
          type: array
          items:
            $ref: '#/components/schemas/batch_ProsodyPrediction'
      required:
      - id
      - predictions
      title: GroupedPredictions<ProsodyPrediction>
    batch_ModelsPredictionsFacemesh:
      type: object
      properties:
        metadata:
          $ref: '#/components/schemas/batch_Null'
        grouped_predictions:
          type: array
          items:
            $ref: '#/components/schemas/batch_GroupedPredictions_FacemeshPrediction'
      required:
      - grouped_predictions
      title: ModelsPredictionsFacemesh
    batch_ProsodyPrediction:
      type: object
      properties:
        text:
          type: string
          description: A segment of text (like a word or a sentence).
        time:
          $ref: '#/components/schemas/batch_TimeInterval'
        confidence:
          type: number
          format: double
          description: Value between `0.0` and `1.0` that indicates our transcription model's relative confidence in this text.
        speaker_confidence:
          type: number
          format: double
          description: Value between `0.0` and `1.0` that indicates our transcription model's relative confidence that this text was spoken by this speaker.
        emotions:
          type: array
          items:
            $ref: '#/components/schemas/batch_EmotionScore'
          description: A high-dimensional embedding in emotion space.
      required:
      - time
      - emotions
      title: ProsodyPrediction
    batch_Status:
      type: string
      enum:
      - QUEUED
      - IN_PROGRESS
      - COMPLETED
      - FAILED
      title: Status
    batch_TranscriptionLanguage:
      type: object
      properties: {}
      description: 'By default, we use an automated language detection method for our Speech Prosody, Language, and NER models. However, if you know what language is being spoken in your media samples, you can specify it via its BCP-47 tag and potentially obtain more accurate results.


        You can specify any of the following languages:

        - Chinese: `zh`

        - Danish: `da`

        - Dutch: `nl`

        - English: `en`

        - English (Australia): `en-AU`

        - English (India): `en-IN`

        - English (New Zealand): `en-NZ`

        - English (United Kingdom): `en-GB`

        - French: `fr`

        - French (Canada): `fr-CA`

        - German: `de`

        - Hindi: `hi`

        - Hindi (Roman Script): `hi-Latn`

        - Indonesian: `id`

        - Italian: `it`

        - Japanese: `ja`

        - Korean: `ko`

        - Norwegian: `no`

        - Polish: `pl`

        - Portuguese: `pt`

        - Portuguese (Brazil): `pt-BR`

        - Portuguese (Portugal): `pt-PT`

        - Russian: `ru`

        - Spanish: `es`

        - Spanish (Latin America): `es-419`

        - Swedish: `sv`

        - Tamil: `ta`

        - Turkish: `tr`

        - Ukrainian: `uk`'
      title: TranscriptionLanguage
    batch_V0BatchJobsGetParametersDirection:
      type: object
      properties: {}
      title: V0BatchJobsGetParametersDirection
    batch_LanguagePrediction:
      type: object
      properties:
        text:
          type: string
          description: A segment of text (like a word or a sentence).
        position:
          $ref: '#/components/schemas/batch_PositionInterval'
        time:
          $ref: '#/components/schemas/batch_TimeInterval'
        confidence:
          type: number
          format: double
          description: Value between `0.0` and `1.0` that indicates our transcription model's relative confidence in this text.
        speaker_confidence:
          type: number
          format: double
          description: Value between `0.0` and `1.0` that indicates our transcription model's relative confidence that this text was spoken by this speaker.
        emotions:
          type: array
          items:
            $ref: '#/components/schemas/batch_EmotionScore'
          description: A high-dimensional embedding in emotion space.
        sentiment:
          type: array
          items:
            $ref: '#/components/schemas/batch_SentimentScore'
          description: 'Sentiment predictions returned as a distribution. This model predicts the probability that a given text could be interpreted as having each sentiment level from `1` (negative) to `9` (positive).


            Compared to returning one estimate of sentiment, this enables a more nuanced analysis of a text''s meaning. For example, a text with very neutral sentiment would have an average rating of `5`. But also a text that could be interpreted as having very positive sentiment or very negative sentiment would also have an average rating of `5`. The average sentiment is less informative than the distribution over sentiment, so this API returns a value for each sentiment level.'
        toxicity:
          type: array
          items:
            $ref: '#/components/schemas/batch_ToxicityScore'
          description: 'Toxicity predictions returned as probabilities that the text can be classified into the following categories: `toxic`, `severe_toxic`, `obscene`, `threat`, `insult`, and `identity_hate`.'
      required:
      - text
      - position
      - emotions
      title: LanguagePrediction
    batch_PositionInterval:
      type: object
      properties:
        begin:
          type: integer
          format: uint64
          description: The index of the first character in the text segment, inclusive.
        end:
          type: integer
          format: uint64
          description: The index of the last character in the text segment, exclusive.
      required:
      - begin
      - end
      description: Position of a segment of text within a larger document, measured in characters. Uses zero-based indexing. The beginning index is inclusive and the end index is exclusive.
      title: PositionInterval
    batch_ModelsPredictionsFace:
      type: object
      properties:
        metadata:
          $ref: '#/components/schemas/batch_Null'
        grouped_predictions:
          type: array
          items:
            $ref: '#/components/schemas/batch_GroupedPredictions_FacePrediction'
      required:
      - grouped_predictions
      title: ModelsPredictionsFace
    batch_ModelsFace:
      type: object
      properties:
        fps_pred:
          type: number
          format: double
          default: 3
          description: Number of frames per second to process. Other frames will be omitted from the response. Set to `0` to process every frame.
        prob_threshold:
          type: number
          format: double
          default: 0.99
          description: Face detection probability threshold. Faces detected with a probability less than this threshold will be omitted from the response.
        identify_faces:
          type: boolean
          default: false
          description: Whether to return identifiers for faces across frames. If `true`, unique identifiers will be assigned to face bounding boxes to differentiate different faces. If `false`, all faces will be tagged with an `unknown` ID.
        min_face_size:
          type: integer
          format: uint64
          description: Minimum bounding box side length in pixels to treat as a face. Faces detected with a bounding box side length in pixels less than this threshold will be omitted from the response.
        facs:
          $ref: '#/components/schemas/batch_FaceFacs'
        descriptions:
          $ref: '#/components/schemas/batch_FaceDescriptions'
        save_faces:
          type: boolean
          default: false
          description: Whether to extract and save the detected faces in the artifacts zip created by each job.
      title: ModelsFace
    batch_V0BatchJobsPostRequestBodyContentMultipartFormDataSchemaJson:
      type: object
      properties:
        models:
          $ref: '#/components/schemas/batch_InferenceBaseRequestModels'
          description: 'Specify the models to use for inference.


            If this field is not explicitly set, then all models will run by default.'
        transcription:
          $ref: '#/components/schemas/batch_InferenceBaseRequestTranscription'
        urls:
          type: array
          items:
            type: string
            format: url
          description: 'URLs to the media files to be processed. Each must be a valid public URL to a media file (see recommended input filetypes) or an archive (`.zip`, `.tar.gz`, `.tar.bz2`, `.tar.xz`) of media files.


            If you wish to supply more than 100 URLs, consider providing them as an archive (`.zip`, `.tar.gz`, `.tar.bz2`, `.tar.xz`).'
        text:
          type: array
          items:
            type: string
          description: Text supplied directly to our Emotional Language and NER models for analysis.
        callback_url:
          type: string
          format: url
          description: If provided, a `POST` request will be made to the URL with the generated predictions on completion or the error message on failure.
        notify:
          type: boolean
          default: false
          description: Whether to send an email notification to the user upon job completion/failure.
      description: Stringified JSON object containing the inference job configuration.
      title: V0BatchJobsPostRequestBodyContentMultipartFormDataSchemaJson
    batch_ModelsPredictionsNer:
      type: object
      properties:
        metadata:
          $ref: '#/components/schemas/batch_TranscriptionMetadata'
        grouped_predictions:
          type: array
          items:
            $ref: '#/components/schemas/batch_GroupedPredictions_NerPrediction'
      required:
      - grouped_predictions
      title: ModelsPredictionsNer
    batch_ModelsPredictionsProsody:
      type: object
      properties:
        metadata:
          $ref: '#/components/schemas/batch_TranscriptionMetadata'
        grouped_predictions:
          type: array
          items:
            $ref: '#/components/schemas/batch_GroupedPredictions_ProsodyPrediction'
      required:
      - grouped_predictions
      title: ModelsPredictionsProsody
    batch_InferencePrediction:
      type: object
      properties:
        file:
          type: string
          description: A file path relative to the top level source URL or file.
        models:
          $ref: '#/components/schemas/batch_ModelsPredictions'
      required:
      - file
      - models
      title: InferencePrediction
    batch_GroupedPredictions_LanguagePrediction:
      type: object
      properties:
        id:
          type: string
          description: An automatically generated label to identify individuals in your media file. Will be `unknown` if you have chosen to disable identification, or if the model is unable to distinguish between individuals.
        predictions:
          type: array
          items:
            $ref: '#/components/schemas/batch_LanguagePrediction'
      required:
      - id
      - predictions
      title: GroupedPredictions<LanguagePrediction>
    batch_UnionPredictResult:
      oneOf:
      - $ref: '#/components/schemas/batch_InferenceSourcePredictResult'
      title: UnionPredictResult
    batch_V0BatchJobsGetParametersSortBy:
      type: object
      properties: {}
      title: V0BatchJobsGetParametersSortBy
    batch_InferenceBaseRequestModels:
      type: object
      properties:
        face:
          $ref: '#/components/schemas/batch_ModelsFace'
        burst:
          $ref: '#/components/schemas/batch_ModelsBurst'
        prosody:
          $ref: '#/components/schemas/batch_ModelsProsody'
        language:
          $ref: '#/components/schemas/batch_ModelsLanguage'
        ner:
          $ref: '#/components/schemas/batch_ModelsNer'
        facemesh:
          $ref: '#/components/schemas/batch_ModelsFacemesh'
      description: 'Specify the models to use for inference.


        If this field is not explicitly set, then all models will run by default.'
      title: InferenceBaseRequestModels
    batch_LanguageGranularity:
      type: object
      properties: {}
      title: LanguageGranularity
    batch_DescriptionsScore:
      type: object
      properties:
        name:
          type: string
          description: Name of the descriptive feature being expressed.
        score:
          type: number
          format: double
          description: Embedding value for the descriptive feature being expressed.
      required:
      - name
      - score
      title: DescriptionsScore
    batch_InferenceRequestModels:
      type: object
      properties:
        face:
          $ref: '#/components/schemas/batch_ModelsFace'
        burst:
          $ref: '#/components/schemas/batch_ModelsBurst'
        prosody:
          $ref: '#/components/schemas/batch_ModelsProsody'
        language:
          $ref: '#/components/schemas/batch_ModelsLanguage'
        ner:
          $ref: '#/components/schemas/batch_ModelsNer'
        facemesh:
          $ref: '#/components/schemas/batch_ModelsFacemesh'
      title: InferenceRequestModels
    batch_InferenceBaseRequestTranscription:
      type: object
      properties:
        language:
          $ref: '#/components/schemas/batch_TranscriptionLanguage'
          description: 'By default, we use an automated language detection method for our Speech Prosody, Language, and NER models. However, if you know what language is being spoken in your media samples, you can specify it via its BCP-47 tag and potentially obtain more accurate results.


            You can specify any of the following languages:

            - Chinese: `zh`

            - Danish: `da`

            - Dutch: `nl`

            - English: `en`

            - English (Australia): `en-AU`

            - English (India): `en-IN`

            - English (New Zealand): `en-NZ`

            - English (United Kingdom): `en-GB`

            - French: `fr`

            - French (Canada): `fr-CA`

            - German: `de`

            - Hindi: `hi`

            - Hindi (Roman Script): `hi-Latn`

            - Indonesian: `id`

            - Italian: `it`

            - Japanese: `ja`

            - Korean: `ko`

            - Norwegian: `no`

            - Polish: `pl`

            - Portuguese: `pt`

            - Portuguese (Brazil): `pt-BR`

            - Portuguese (Portugal): `pt-PT`

            - Russian: `ru`

            - Spanish: `es`

            - Spanish (Latin America): `es-419`

            - Swedish: `sv`

            - Tamil: `ta`

            - Turkish: `tr`

            - Ukrainian: `uk`'
        identify_speakers:
          type: boolean
          default: false
          description: Whether to return identifiers for speakers over time. If `true`, unique identifiers will be assigned 

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