speech_to_text_v1.rb

# frozen_string_literal: true

# (C) Copyright IBM Corp. 2018, 2022.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# IBM OpenAPI SDK Code Generator Version: 3.38.0-07189efd-20210827-205025
#
# The IBM Watson™ Speech to Text service provides APIs that use IBM's
# speech-recognition capabilities to produce transcripts of spoken audio.  The service can
# transcribe speech from various languages and audio formats. In addition to basic
# transcription, the service can produce detailed information about many different aspects
# of the audio. It returns all JSON response content in the UTF-8 character set.
#
# The service supports two types of models: previous-generation models that include the
# terms `Broadband` and `Narrowband` in their names, and next-generation models that
# include the terms `Multimedia` and `Telephony` in their names. Broadband and multimedia
# models have minimum sampling rates of 16 kHz. Narrowband and telephony models have
# minimum sampling rates of 8 kHz. The next-generation models offer high throughput and
# greater transcription accuracy.
#
# Effective 15 March 2022, previous-generation models for all languages other than Arabic
# and Japanese are deprecated. The deprecated models remain available until 15 September
# 2022, when they will be removed from the service and the documentation. You must migrate
# to the equivalent next-generation model by the end of service date. For more
# information, see [Migrating to next-generation
# models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-migrate).{:
# deprecated}
#
# For speech recognition, the service supports synchronous and asynchronous HTTP
# Representational State Transfer (REST) interfaces. It also supports a WebSocket
# interface that provides a full-duplex, low-latency communication channel: Clients send
# requests and audio to the service and receive results over a single connection
# asynchronously.
#
# The service also offers two customization interfaces. Use language model customization
# to expand the vocabulary of a base model with domain-specific terminology. Use acoustic
# model customization to adapt a base model for the acoustic characteristics of your
# audio. For language model customization, the service also supports grammars. A grammar
# is a formal language specification that lets you restrict the phrases that the service
# can recognize.
#
# Language model customization and grammars are available for most previous- and
# next-generation models. Acoustic model customization is available for all
# previous-generation models.

require "concurrent"
require "erb"
require "json"
require "ibm_cloud_sdk_core"
require_relative "./common.rb"

module IBMWatson
  ##
  # The Speech to Text V1 service.
  class SpeechToTextV1 < IBMCloudSdkCore::BaseService
    include Concurrent::Async
    DEFAULT_SERVICE_NAME = "speech_to_text"
    DEFAULT_SERVICE_URL = "https://api.us-south.speech-to-text.watson.cloud.ibm.com"
    ##
    # @!method initialize(args)
    # Construct a new client for the Speech to Text service.
    #
    # @param args [Hash] The args to initialize with
    # @option args service_url [String] The base service URL to use when contacting the service.
    #   The base service_url may differ between IBM Cloud regions.
    # @option args authenticator [Object] The Authenticator instance to be configured for this service.
    # @option args service_name [String] The name of the service to configure. Will be used as the key to load
    #   any external configuration, if applicable.
    def initialize(args = {})
      @__async_initialized__ = false
      defaults = {}
      defaults[:service_url] = DEFAULT_SERVICE_URL
      defaults[:service_name] = DEFAULT_SERVICE_NAME
      defaults[:authenticator] = nil
      user_service_url = args[:service_url] unless args[:service_url].nil?
      args = defaults.merge(args)
      args[:authenticator] = IBMCloudSdkCore::ConfigBasedAuthenticatorFactory.new.get_authenticator(service_name: args[:service_name]) if args[:authenticator].nil?
      super
      @service_url = user_service_url unless user_service_url.nil?
    end

    #########################
    # Models
    #########################

    ##
    # @!method list_models
    # List models.
    # Lists all language models that are available for use with the service. The
    #   information includes the name of the model and its minimum sampling rate in Hertz,
    #   among other things. The ordering of the list of models can change from call to
    #   call; do not rely on an alphabetized or static list of models.
    #
    #   **See also:** [Listing all
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-list#models-list-all).
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def list_models
      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "list_models")
      headers.merge!(sdk_headers)

      method_url = "/v1/models"

      response = request(
        method: "GET",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      response
    end

    ##
    # @!method get_model(model_id:)
    # Get a model.
    # Gets information for a single specified language model that is available for use
    #   with the service. The information includes the name of the model and its minimum
    #   sampling rate in Hertz, among other things.
    #
    #   **See also:** [Listing a specific
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-list#models-list-specific).
    # @param model_id [String] The identifier of the model in the form of its name from the output of the [List
    #   models](#listmodels) method. (**Note:** The model `ar-AR_BroadbandModel` is
    #   deprecated; use `ar-MS_BroadbandModel` instead.).
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def get_model(model_id:)
      raise ArgumentError.new("model_id must be provided") if model_id.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "get_model")
      headers.merge!(sdk_headers)

      method_url = "/v1/models/%s" % [ERB::Util.url_encode(model_id)]

      response = request(
        method: "GET",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      response
    end
    #########################
    # Synchronous
    #########################

    ##
    # @!method recognize(audio:, content_type: nil, model: nil, language_customization_id: nil, acoustic_customization_id: nil, base_model_version: nil, customization_weight: nil, inactivity_timeout: nil, keywords: nil, keywords_threshold: nil, max_alternatives: nil, word_alternatives_threshold: nil, word_confidence: nil, timestamps: nil, profanity_filter: nil, smart_formatting: nil, speaker_labels: nil, customization_id: nil, grammar_name: nil, redaction: nil, audio_metrics: nil, end_of_phrase_silence_time: nil, split_transcript_at_phrase_end: nil, speech_detector_sensitivity: nil, background_audio_suppression: nil, low_latency: nil)
    # Recognize audio.
    # Sends audio and returns transcription results for a recognition request. You can
    #   pass a maximum of 100 MB and a minimum of 100 bytes of audio with a request. The
    #   service automatically detects the endianness of the incoming audio and, for audio
    #   that includes multiple channels, downmixes the audio to one-channel mono during
    #   transcoding. The method returns only final results; to enable interim results, use
    #   the WebSocket API. (With the `curl` command, use the `--data-binary` option to
    #   upload the file for the request.)
    #
    #   **See also:** [Making a basic HTTP
    #   request](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-http#HTTP-basic).
    #
    #
    #   ### Streaming mode
    #
    #    For requests to transcribe live audio as it becomes available, you must set the
    #   `Transfer-Encoding` header to `chunked` to use streaming mode. In streaming mode,
    #   the service closes the connection (status code 408) if it does not receive at
    #   least 15 seconds of audio (including silence) in any 30-second period. The service
    #   also closes the connection (status code 400) if it detects no speech for
    #   `inactivity_timeout` seconds of streaming audio; use the `inactivity_timeout`
    #   parameter to change the default of 30 seconds.
    #
    #   **See also:**
    #   * [Audio
    #   transmission](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-input#transmission)
    #   *
    #   [Timeouts](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-input#timeouts)
    #
    #
    #   ### Audio formats (content types)
    #
    #    The service accepts audio in the following formats (MIME types).
    #   * For formats that are labeled **Required**, you must use the `Content-Type`
    #   header with the request to specify the format of the audio.
    #   * For all other formats, you can omit the `Content-Type` header or specify
    #   `application/octet-stream` with the header to have the service automatically
    #   detect the format of the audio. (With the `curl` command, you can specify either
    #   `"Content-Type:"` or `"Content-Type: application/octet-stream"`.)
    #
    #   Where indicated, the format that you specify must include the sampling rate and
    #   can optionally include the number of channels and the endianness of the audio.
    #   * `audio/alaw` (**Required.** Specify the sampling rate (`rate`) of the audio.)
    #   * `audio/basic` (**Required.** Use only with narrowband models.)
    #   * `audio/flac`
    #   * `audio/g729` (Use only with narrowband models.)
    #   * `audio/l16` (**Required.** Specify the sampling rate (`rate`) and optionally the
    #   number of channels (`channels`) and endianness (`endianness`) of the audio.)
    #   * `audio/mp3`
    #   * `audio/mpeg`
    #   * `audio/mulaw` (**Required.** Specify the sampling rate (`rate`) of the audio.)
    #   * `audio/ogg` (The service automatically detects the codec of the input audio.)
    #   * `audio/ogg;codecs=opus`
    #   * `audio/ogg;codecs=vorbis`
    #   * `audio/wav` (Provide audio with a maximum of nine channels.)
    #   * `audio/webm` (The service automatically detects the codec of the input audio.)
    #   * `audio/webm;codecs=opus`
    #   * `audio/webm;codecs=vorbis`
    #
    #   The sampling rate of the audio must match the sampling rate of the model for the
    #   recognition request: for broadband models, at least 16 kHz; for narrowband models,
    #   at least 8 kHz. If the sampling rate of the audio is higher than the minimum
    #   required rate, the service down-samples the audio to the appropriate rate. If the
    #   sampling rate of the audio is lower than the minimum required rate, the request
    #   fails.
    #
    #    **See also:** [Supported audio
    #   formats](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-audio-formats).
    #
    #
    #   ### Next-generation models
    #
    #    The service supports next-generation `Multimedia` (16 kHz) and `Telephony` (8
    #   kHz) models for many languages. Next-generation models have higher throughput than
    #   the service's previous generation of `Broadband` and `Narrowband` models. When you
    #   use next-generation models, the service can return transcriptions more quickly and
    #   also provide noticeably better transcription accuracy.
    #
    #   You specify a next-generation model by using the `model` query parameter, as you
    #   do a previous-generation model. Many next-generation models also support the
    #   `low_latency` parameter, which is not available with previous-generation models.
    #   Next-generation models do not support all of the parameters that are available for
    #   use with previous-generation models.
    #
    #   **Important:** Effective 15 March 2022, previous-generation models for all
    #   languages other than Arabic and Japanese are deprecated. The deprecated models
    #   remain available until 15 September 2022, when they will be removed from the
    #   service and the documentation. You must migrate to the equivalent next-generation
    #   model by the end of service date. For more information, see [Migrating to
    #   next-generation
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-migrate).
    #
    #
    #   **See also:**
    #   * [Next-generation languages and
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-ng)
    #   * [Supported features for next-generation
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-ng#models-ng-features)
    #
    #
    #   ### Multipart speech recognition
    #
    #    **Note:** The asynchronous HTTP interface, WebSocket interface, and Watson SDKs
    #   do not support multipart speech recognition.
    #
    #   The HTTP `POST` method of the service also supports multipart speech recognition.
    #   With multipart requests, you pass all audio data as multipart form data. You
    #   specify some parameters as request headers and query parameters, but you pass JSON
    #   metadata as form data to control most aspects of the transcription. You can use
    #   multipart recognition to pass multiple audio files with a single request.
    #
    #   Use the multipart approach with browsers for which JavaScript is disabled or when
    #   the parameters used with the request are greater than the 8 KB limit imposed by
    #   most HTTP servers and proxies. You can encounter this limit, for example, if you
    #   want to spot a very large number of keywords.
    #
    #   **See also:** [Making a multipart HTTP
    #   request](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-http#HTTP-multi).
    # @param audio [File] The audio to transcribe.
    # @param content_type [String] The format (MIME type) of the audio. For more information about specifying an
    #   audio format, see **Audio formats (content types)** in the method description.
    # @param model [String] The identifier of the model that is to be used for the recognition request.
    #   (**Note:** The model `ar-AR_BroadbandModel` is deprecated; use
    #   `ar-MS_BroadbandModel` instead.) See [Using a model for speech
    #   recognition](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-use).
    # @param language_customization_id [String] The customization ID (GUID) of a custom language model that is to be used with the
    #   recognition request. The base model of the specified custom language model must
    #   match the model specified with the `model` parameter. You must make the request
    #   with credentials for the instance of the service that owns the custom model. By
    #   default, no custom language model is used. See [Using a custom language model for
    #   speech
    #   recognition](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-languageUse).
    #
    #
    #   **Note:** Use this parameter instead of the deprecated `customization_id`
    #   parameter.
    # @param acoustic_customization_id [String] The customization ID (GUID) of a custom acoustic model that is to be used with the
    #   recognition request. The base model of the specified custom acoustic model must
    #   match the model specified with the `model` parameter. You must make the request
    #   with credentials for the instance of the service that owns the custom model. By
    #   default, no custom acoustic model is used. See [Using a custom acoustic model for
    #   speech
    #   recognition](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-acousticUse).
    # @param base_model_version [String] The version of the specified base model that is to be used with the recognition
    #   request. Multiple versions of a base model can exist when a model is updated for
    #   internal improvements. The parameter is intended primarily for use with custom
    #   models that have been upgraded for a new base model. The default value depends on
    #   whether the parameter is used with or without a custom model. See [Making speech
    #   recognition requests with upgraded custom
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-upgrade-use#custom-upgrade-use-recognition).
    # @param customization_weight [Float] If you specify the customization ID (GUID) of a custom language model with the
    #   recognition request, the customization weight tells the service how much weight to
    #   give to words from the custom language model compared to those from the base model
    #   for the current request.
    #
    #   Specify a value between 0.0 and 1.0. Unless a different customization weight was
    #   specified for the custom model when it was trained, the default value is 0.3. A
    #   customization weight that you specify overrides a weight that was specified when
    #   the custom model was trained.
    #
    #   The default value yields the best performance in general. Assign a higher value if
    #   your audio makes frequent use of OOV words from the custom model. Use caution when
    #   setting the weight: a higher value can improve the accuracy of phrases from the
    #   custom model's domain, but it can negatively affect performance on non-domain
    #   phrases.
    #
    #   See [Using customization
    #   weight](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-languageUse#weight).
    # @param inactivity_timeout [Fixnum] The time in seconds after which, if only silence (no speech) is detected in
    #   streaming audio, the connection is closed with a 400 error. The parameter is
    #   useful for stopping audio submission from a live microphone when a user simply
    #   walks away. Use `-1` for infinity. See [Inactivity
    #   timeout](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-input#timeouts-inactivity).
    # @param keywords [Array[String]] An array of keyword strings to spot in the audio. Each keyword string can include
    #   one or more string tokens. Keywords are spotted only in the final results, not in
    #   interim hypotheses. If you specify any keywords, you must also specify a keywords
    #   threshold. Omit the parameter or specify an empty array if you do not need to spot
    #   keywords.
    #
    #   You can spot a maximum of 1000 keywords with a single request. A single keyword
    #   can have a maximum length of 1024 characters, though the maximum effective length
    #   for double-byte languages might be shorter. Keywords are case-insensitive.
    #
    #   See [Keyword
    #   spotting](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-spotting#keyword-spotting).
    # @param keywords_threshold [Float] A confidence value that is the lower bound for spotting a keyword. A word is
    #   considered to match a keyword if its confidence is greater than or equal to the
    #   threshold. Specify a probability between 0.0 and 1.0. If you specify a threshold,
    #   you must also specify one or more keywords. The service performs no keyword
    #   spotting if you omit either parameter. See [Keyword
    #   spotting](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-spotting#keyword-spotting).
    # @param max_alternatives [Fixnum] The maximum number of alternative transcripts that the service is to return. By
    #   default, the service returns a single transcript. If you specify a value of `0`,
    #   the service uses the default value, `1`. See [Maximum
    #   alternatives](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-metadata#max-alternatives).
    # @param word_alternatives_threshold [Float] A confidence value that is the lower bound for identifying a hypothesis as a
    #   possible word alternative (also known as "Confusion Networks"). An alternative
    #   word is considered if its confidence is greater than or equal to the threshold.
    #   Specify a probability between 0.0 and 1.0. By default, the service computes no
    #   alternative words. See [Word
    #   alternatives](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-spotting#word-alternatives).
    # @param word_confidence [Boolean] If `true`, the service returns a confidence measure in the range of 0.0 to 1.0 for
    #   each word. By default, the service returns no word confidence scores. See [Word
    #   confidence](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-metadata#word-confidence).
    # @param timestamps [Boolean] If `true`, the service returns time alignment for each word. By default, no
    #   timestamps are returned. See [Word
    #   timestamps](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-metadata#word-timestamps).
    # @param profanity_filter [Boolean] If `true`, the service filters profanity from all output except for keyword
    #   results by replacing inappropriate words with a series of asterisks. Set the
    #   parameter to `false` to return results with no censoring.
    #
    #   **Note:** The parameter can be used with US English and Japanese transcription
    #   only. See [Profanity
    #   filtering](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-formatting#profanity-filtering).
    # @param smart_formatting [Boolean] If `true`, the service converts dates, times, series of digits and numbers, phone
    #   numbers, currency values, and internet addresses into more readable, conventional
    #   representations in the final transcript of a recognition request. For US English,
    #   the service also converts certain keyword strings to punctuation symbols. By
    #   default, the service performs no smart formatting.
    #
    #   **Note:** The parameter can be used with US English, Japanese, and Spanish (all
    #   dialects) transcription only.
    #
    #   See [Smart
    #   formatting](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-formatting#smart-formatting).
    # @param speaker_labels [Boolean] If `true`, the response includes labels that identify which words were spoken by
    #   which participants in a multi-person exchange. By default, the service returns no
    #   speaker labels. Setting `speaker_labels` to `true` forces the `timestamps`
    #   parameter to be `true`, regardless of whether you specify `false` for the
    #   parameter.
    #   * _For previous-generation models,_ the parameter can be used with Australian
    #   English, US English, German, Japanese, Korean, and Spanish (both broadband and
    #   narrowband models) and UK English (narrowband model) transcription only.
    #   * _For next-generation models,_ the parameter can be used with Czech, English
    #   (Australian, Indian, UK, and US), German, Japanese, Korean, and Spanish
    #   transcription only.
    #
    #   See [Speaker
    #   labels](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-speaker-labels).
    # @param customization_id [String] **Deprecated.** Use the `language_customization_id` parameter to specify the
    #   customization ID (GUID) of a custom language model that is to be used with the
    #   recognition request. Do not specify both parameters with a request.
    # @param grammar_name [String] The name of a grammar that is to be used with the recognition request. If you
    #   specify a grammar, you must also use the `language_customization_id` parameter to
    #   specify the name of the custom language model for which the grammar is defined.
    #   The service recognizes only strings that are recognized by the specified grammar;
    #   it does not recognize other custom words from the model's words resource.
    #
    #   See [Using a grammar for speech
    #   recognition](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-grammarUse).
    # @param redaction [Boolean] If `true`, the service redacts, or masks, numeric data from final transcripts. The
    #   feature redacts any number that has three or more consecutive digits by replacing
    #   each digit with an `X` character. It is intended to redact sensitive numeric data,
    #   such as credit card numbers. By default, the service performs no redaction.
    #
    #   When you enable redaction, the service automatically enables smart formatting,
    #   regardless of whether you explicitly disable that feature. To ensure maximum
    #   security, the service also disables keyword spotting (ignores the `keywords` and
    #   `keywords_threshold` parameters) and returns only a single final transcript
    #   (forces the `max_alternatives` parameter to be `1`).
    #
    #   **Note:** The parameter can be used with US English, Japanese, and Korean
    #   transcription only.
    #
    #   See [Numeric
    #   redaction](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-formatting#numeric-redaction).
    # @param audio_metrics [Boolean] If `true`, requests detailed information about the signal characteristics of the
    #   input audio. The service returns audio metrics with the final transcription
    #   results. By default, the service returns no audio metrics.
    #
    #   See [Audio
    #   metrics](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-metrics#audio-metrics).
    # @param end_of_phrase_silence_time [Float] If `true`, specifies the duration of the pause interval at which the service
    #   splits a transcript into multiple final results. If the service detects pauses or
    #   extended silence before it reaches the end of the audio stream, its response can
    #   include multiple final results. Silence indicates a point at which the speaker
    #   pauses between spoken words or phrases.
    #
    #   Specify a value for the pause interval in the range of 0.0 to 120.0.
    #   * A value greater than 0 specifies the interval that the service is to use for
    #   speech recognition.
    #   * A value of 0 indicates that the service is to use the default interval. It is
    #   equivalent to omitting the parameter.
    #
    #   The default pause interval for most languages is 0.8 seconds; the default for
    #   Chinese is 0.6 seconds.
    #
    #   See [End of phrase silence
    #   time](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-parsing#silence-time).
    # @param split_transcript_at_phrase_end [Boolean] If `true`, directs the service to split the transcript into multiple final results
    #   based on semantic features of the input, for example, at the conclusion of
    #   meaningful phrases such as sentences. The service bases its understanding of
    #   semantic features on the base language model that you use with a request. Custom
    #   language models and grammars can also influence how and where the service splits a
    #   transcript.
    #
    #   By default, the service splits transcripts based solely on the pause interval. If
    #   the parameters are used together on the same request, `end_of_phrase_silence_time`
    #   has precedence over `split_transcript_at_phrase_end`.
    #
    #   See [Split transcript at phrase
    #   end](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-parsing#split-transcript).
    # @param speech_detector_sensitivity [Float] The sensitivity of speech activity detection that the service is to perform. Use
    #   the parameter to suppress word insertions from music, coughing, and other
    #   non-speech events. The service biases the audio it passes for speech recognition
    #   by evaluating the input audio against prior models of speech and non-speech
    #   activity.
    #
    #   Specify a value between 0.0 and 1.0:
    #   * 0.0 suppresses all audio (no speech is transcribed).
    #   * 0.5 (the default) provides a reasonable compromise for the level of sensitivity.
    #   * 1.0 suppresses no audio (speech detection sensitivity is disabled).
    #
    #   The values increase on a monotonic curve.
    #
    #   The parameter is supported with all next-generation models and with most
    #   previous-generation models. See [Speech detector
    #   sensitivity](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-detection#detection-parameters-sensitivity)
    #   and [Language model
    #   support](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-detection#detection-support).
    # @param background_audio_suppression [Float] The level to which the service is to suppress background audio based on its volume
    #   to prevent it from being transcribed as speech. Use the parameter to suppress side
    #   conversations or background noise.
    #
    #   Specify a value in the range of 0.0 to 1.0:
    #   * 0.0 (the default) provides no suppression (background audio suppression is
    #   disabled).
    #   * 0.5 provides a reasonable level of audio suppression for general usage.
    #   * 1.0 suppresses all audio (no audio is transcribed).
    #
    #   The values increase on a monotonic curve.
    #
    #   The parameter is supported with all next-generation models and with most
    #   previous-generation models. See [Background audio
    #   suppression](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-detection#detection-parameters-suppression)
    #   and [Language model
    #   support](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-detection#detection-support).
    # @param low_latency [Boolean] If `true` for next-generation `Multimedia` and `Telephony` models that support low
    #   latency, directs the service to produce results even more quickly than it usually
    #   does. Next-generation models produce transcription results faster than
    #   previous-generation models. The `low_latency` parameter causes the models to
    #   produce results even more quickly, though the results might be less accurate when
    #   the parameter is used.
    #
    #   The parameter is not available for previous-generation `Broadband` and
    #   `Narrowband` models. It is available only for some next-generation models. For a
    #   list of next-generation models that support low latency, see [Supported
    #   next-generation language
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-ng#models-ng-supported).
    #   * For more information about the `low_latency` parameter, see [Low
    #   latency](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-interim#low-latency).
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def recognize(audio:, content_type: nil, model: nil, language_customization_id: nil, acoustic_customization_id: nil, base_model_version: nil, customization_weight: nil, inactivity_timeout: nil, keywords: nil, keywords_threshold: nil, max_alternatives: nil, word_alternatives_threshold: nil, word_confidence: nil, timestamps: nil, profanity_filter: nil, smart_formatting: nil, speaker_labels: nil, customization_id: nil, grammar_name: nil, redaction: nil, audio_metrics: nil, end_of_phrase_silence_time: nil, split_transcript_at_phrase_end: nil, speech_detector_sensitivity: nil, background_audio_suppression: nil, low_latency: nil)
      raise ArgumentError.new("audio must be provided") if audio.nil?

      headers = {
        "Content-Type" => content_type
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "recognize")
      headers.merge!(sdk_headers)
      keywords *= "," unless keywords.nil?

      params = {
        "model" => model,
        "language_customization_id" => language_customization_id,
        "acoustic_customization_id" => acoustic_customization_id,
        "base_model_version" => base_model_version,
        "customization_weight" => customization_weight,
        "inactivity_timeout" => inactivity_timeout,
        "keywords" => keywords,
        "keywords_threshold" => keywords_threshold,
        "max_alternatives" => max_alternatives,
        "word_alternatives_threshold" => word_alternatives_threshold,
        "word_confidence" => word_confidence,
        "timestamps" => timestamps,
        "profanity_filter" => profanity_filter,
        "smart_formatting" => smart_formatting,
        "speaker_labels" => speaker_labels,
        "customization_id" => customization_id,
        "grammar_name" => grammar_name,
        "redaction" => redaction,
        "audio_metrics" => audio_metrics,
        "end_of_phrase_silence_time" => end_of_phrase_silence_time,
        "split_transcript_at_phrase_end" => split_transcript_at_phrase_end,
        "speech_detector_sensitivity" => speech_detector_sensitivity,
        "background_audio_suppression" => background_audio_suppression,
        "low_latency" => low_latency
      }

      data = audio

      method_url = "/v1/recognize"

      response = request(
        method: "POST",
        url: method_url,
        headers: headers,
        params: params,
        data: data,
        accept_json: true
      )
      response
    end

    ##
    # @!method recognize_using_websocket(content_type: nil,recognize_callback:,audio: nil,chunk_data: false,model: nil,customization_id: nil,acoustic_customization_id: nil,customization_weight: nil,base_model_version: nil,inactivity_timeout: nil,interim_results: nil,keywords: nil,keywords_threshold: nil,max_alternatives: nil,word_alternatives_threshold: nil,word_confidence: nil,timestamps: nil,profanity_filter: nil,smart_formatting: nil,speaker_labels: nil, end_of_phrase_silence_time: nil, split_transcript_at_phrase_end: nil, speech_detector_sensitivity: nil, background_audio_suppression: nil, low_latency: nil)
    # Sends audio for speech recognition using web sockets.
    # @param content_type [String] The type of the input: audio/basic, audio/flac, audio/l16, audio/mp3, audio/mpeg, audio/mulaw, audio/ogg, audio/ogg;codecs=opus, audio/ogg;codecs=vorbis, audio/wav, audio/webm, audio/webm;codecs=opus, audio/webm;codecs=vorbis, or multipart/form-data.
    # @param recognize_callback [RecognizeCallback] The instance handling events returned from the service.
    # @param audio [IO] Audio to transcribe in the format specified by the `Content-Type` header.
    # @param chunk_data [Boolean] If true, then the WebSocketClient will expect to receive data in chunks rather than as a single audio file
    # @param model [String] The identifier of the model to be used for the recognition request.
    # @param customization_id [String] The GUID of a custom language model that is to be used with the request. The base model of the specified custom language model must match the model specified with the `model` parameter. You must make the request with service credentials created for the instance of the service that owns the custom model. By default, no custom language model is used.
    # @param acoustic_customization_id [String] The GUID of a custom acoustic model that is to be used with the request. The base model of the specified custom acoustic model must match the model specified with the `model` parameter. You must make the request with service credentials created for the instance of the service that owns the custom model. By default, no custom acoustic model is used.
    # @param language_customization_id [String] The GUID of a custom language model that is to be used with the request. The base model of the specified custom language model must match the model specified with the `model` parameter. You must make the request with service credentials created for the instance of the service that owns the custom model. By default, no custom language model is used.
    # @param base_model_version [String] The version of the specified base `model` that is to be used for speech recognition. Multiple versions of a base model can exist when a model is updated for internal improvements. The parameter is intended primarily for use with custom models that have been upgraded for a new base model. The default value depends on whether the parameter is used with or without a custom model. For more information, see [Base model version](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-input#version).
    # @param inactivity_timeout [Integer] The time in seconds after which, if only silence (no speech) is detected in submitted audio, the connection is closed with a 400 error. Useful for stopping audio submission from a live microphone when a user simply walks away. Use `-1` for infinity.
    # @param interim_results [Boolean] Send back non-final previews of each "sentence" as it is being processed. These results are ignored in text mode.
    # @param keywords [Array<String>] Array of keyword strings to spot in the audio. Each keyword string can include one or more tokens. Keywords are spotted only in the final hypothesis, not in interim results. If you specify any keywords, you must also specify a keywords threshold. Omit the parameter or specify an empty array if you do not need to spot keywords.
    # @param keywords_threshold [Float] Confidence value that is the lower bound for spotting a keyword. A word is considered to match a keyword if its confidence is greater than or equal to the threshold. Specify a probability between 0 and 1 inclusive. No keyword spotting is performed if you omit the parameter. If you specify a threshold, you must also specify one or more keywords.
    # @param max_alternatives [Integer] Maximum number of alternative transcripts to be returned. By default, a single transcription is returned.
    # @param word_alternatives_threshold [Float] Confidence value that is the lower bound for identifying a hypothesis as a possible word alternative (also known as \"Confusion Networks\"). An alternative word is considered if its confidence is greater than or equal to the threshold. Specify a probability between 0 and 1 inclusive. No alternative words are computed if you omit the parameter.
    # @param word_confidence [Boolean] If `true`, confidence measure per word is returned.
    # @param timestamps [Boolean] If `true`, time alignment for each word is returned.
    # @param profanity_filter [Boolean] If `true` (the default), filters profanity from all output except for keyword results by replacing inappropriate words with a series of asterisks. Set the parameter to `false` to return results with no censoring. Applies to US English transcription only.
    # @param smart_formatting [Boolean] If `true`, converts dates, times, series of digits and numbers, phone numbers, currency values, and Internet addresses into more readable, conventional representations in the final transcript of a recognition request. If `false` (the default), no formatting is performed. Applies to US English transcription only.
    # @param speaker_labels [Boolean] Indicates whether labels that identify which words were spoken by which participants in a multi-person exchange are to be included in the response. The default is `false`; no speaker labels are returned. Setting `speaker_labels` to `true` forces the `timestamps` parameter to be `true`, regardless of whether you specify `false` for the parameter.   To determine whether a language model supports speaker labels, use the `GET /v1/models` method and check that the attribute `speaker_labels` is set to `true`. You can also refer to [Speaker labels](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-output#speaker_labels).
    # @param grammar_name [String] The name of a grammar that is to be used with the recognition request. If you
    #   specify a grammar, you must also use the `language_customization_id` parameter to
    #   specify the name of the custom language model for which the grammar is defined.
    #   The service recognizes only strings that are recognized by the specified grammar;
    #   it does not recognize other custom words from the model's words resource. See
    #   [Grammars](https://cloud.ibm.com/docs/speech-to-text/output.html).
    # @param redaction [Boolean] If `true`, the service redacts, or masks, numeric data from final transcripts. The
    #   feature redacts any number that has three or more consecutive digits by replacing
    #   each digit with an `X` character. It is intended to redact sensitive numeric data,
    #   such as credit card numbers. By default, the service performs no redaction.
    #
    #   When you enable redaction, the service automatically enables smart formatting,
    #   regardless of whether you explicitly disable that feature. To ensure maximum
    #   security, the service also disables keyword spotting (ignores the `keywords` and
    #   `keywords_threshold` parameters) and returns only a single final transcript
    #   (forces the `max_alternatives` parameter to be `1`).
    #
    #   **Note:** Applies to US English, Japanese, and Korean transcription only.
    #
    #   See [Numeric
    #   redaction](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-output#redaction).
    #
    # @param processing_metrics [Boolean] If `true`, requests processing metrics about the service's transcription of the
    #   input audio. The service returns processing metrics at the interval specified by
    #   the `processing_metrics_interval` parameter. It also returns processing metrics
    #   for transcription events, for example, for final and interim results. By default,
    #   the service returns no processing metrics.
    # @param processing_metrics_interval [Float] Specifies the interval in real wall-clock seconds at which the service is to
    #   return processing metrics. The parameter is ignored unless the
    #   `processing_metrics` parameter is set to `true`.    #   The parameter accepts a minimum value of 0.1 seconds. The level of precision is
    #   not restricted, so you can specify values such as 0.25 and 0.125.
    #
    #   The service does not impose a maximum value. If you want to receive processing
    #   metrics only for transcription events instead of at periodic intervals, set the
    #   value to a large number. If the value is larger than the duration of the audio,
    #   the service returns processing metrics only for transcription events.
    # @param audio_metrics [Boolean] If `true`, requests detailed information about the signal characteristics of the
    #   input audio. The service returns audio metrics with the final transcription
    #   results. By default, the service returns no audio metrics.
    # @return [WebSocketClient] Returns a new WebSocketClient object
    #
    #   See [Audio
    #   metrics](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-metrics#audio_metrics).
    # @param end_of_phrase_silence_time [Float] If `true`, specifies the duration of the pause interval at which the service
    #   splits a transcript into multiple final results. If the service detects pauses or
    #   extended silence before it reaches the end of the audio stream, its response can
    #   include multiple final results. Silence indicates a point at which the speaker
    #   pauses between spoken words or phrases.
    #
    #   Specify a value for the pause interval in the range of 0.0 to 120.0.
    #   * A value greater than 0 specifies the interval that the service is to use for
    #   speech recognition.
    #   * A value of 0 indicates that the service is to use the default interval. It is
    #   equivalent to omitting the parameter.
    #
    #   The default pause interval for most languages is 0.8 seconds; the default for
    #   Chinese is 0.6 seconds.
    #
    #   See [End of phrase silence
    #   time](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-output#silence_time).
    # @param split_transcript_at_phrase_end [Boolean] If `true`, directs the service to split the transcript into multiple final results
    #   based on semantic features of the input, for example, at the conclusion of
    #   meaningful phrases such as sentences. The service bases its understanding of
    #   semantic features on the base language model that you use with a request. Custom
    #   language models and grammars can also influence how and where the service splits a
    #   transcript. By default, the service splits transcripts based solely on the pause
    #   interval.
    #
    #   See [Split transcript at phrase
    #   end](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-output#split_transcript).
    # @param speech_detector_sensitivity [Float] The sensitivity of speech activity detection that the service is to perform. Use
    #   the parameter to suppress word insertions from music, coughing, and other
    #   non-speech events. The service biases the audio it passes for speech recognition
    #   by evaluating the input audio against prior models of speech and non-speech
    #   activity.
    #
    #   Specify a value between 0.0 and 1.0:
    #   * 0.0 suppresses all audio (no speech is transcribed).
    #   * 0.5 (the default) provides a reasonable compromise for the level of sensitivity.
    #   * 1.0 suppresses no audio (speech detection sensitivity is disabled).
    #
    #   The values increase on a monotonic curve. See [Speech Activity
    #   Detection](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-input#detection).
    # @param background_audio_suppression [Float] The level to which the service is to suppress background audio based on its volume
    #   to prevent it from being transcribed as speech. Use the parameter to suppress side
    #   conversations or background noise.
    #
    #   Specify a value in the range of 0.0 to 1.0:
    #   * 0.0 (the default) provides no suppression (background audio suppression is
    #   disabled).
    #   * 0.5 provides a reasonable level of audio suppression for general usage.
    #   * 1.0 suppresses all audio (no audio is transcribed).
    #
    #   The values increase on a monotonic curve. See [Speech Activity
    #   Detection](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-input#detection).
    # @param low_latency [Boolean] If `true` for next-generation `Multimedia` and `Telephony` models that support low
    #   latency, directs the service to produce results even more quickly than it usually
    #   does. Next-generation models produce transcription results faster than
    #   previous-generation models. The `low_latency` parameter causes the models to
    #   produce results even more quickly, though the results might be less accurate when
    #   the parameter is used.
    #
    #   **Note:** The parameter is beta functionality. It is not available for
    #   previous-generation `Broadband` and `Narrowband` models. It is available only for
    #   some next-generation models.
    #
    #   * For a list of next-generation models that support low latency, see [Supported
    #   language
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-ng#models-ng-supported)
    #   for next-generation models.
    #   * For more information about the `low_latency` parameter, see [Low
    #   latency](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-interim#low-latency).
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def recognize_using_websocket(
      content_type: nil,
      recognize_callback:,
      audio: nil,
      chunk_data: false,
      model: nil,
      language_customization_id: nil,
      customization_id: nil,
      acoustic_customization_id: nil,
      customization_weight: nil,
      base_model_version: nil,
      inactivity_timeout: nil,
      interim_results: nil,
      keywords: nil,
      keywords_threshold: nil,
      max_alternatives: nil,
      word_alternatives_threshold: nil,
      word_confidence: nil,
      timestamps: nil,
      profanity_filter: nil,
      smart_formatting: nil,
      speaker_labels: nil,
      grammar_name: nil,
      redaction: nil,
      processing_metrics: nil,
      processing_metrics_interval: nil,
      audio_metrics: nil,
      end_of_phrase_silence_time: nil,
      split_transcript_at_phrase_end: nil,
      speech_detector_sensitivity: nil,
      background_audio_suppression: nil,
      low_latency: nil
    )
      raise ArgumentError("Audio must be provided") if audio.nil? && !chunk_data
      raise ArgumentError("Recognize callback must be provided") if recognize_callback.nil?
      raise TypeError("Callback is not a derived class of RecognizeCallback") unless recognize_callback.is_a?(IBMWatson::RecognizeCallback)

      require_relative("./websocket/speech_to_text_websocket_listener.rb")
      headers = {}
      headers = conn.default_options.headers.to_hash unless conn.default_options.headers.to_hash.empty?
      @authenticator.authenticate(headers)
      service_url = @service_url.gsub("https:", "wss:")
      params = {
        "model" => model,
        "customization_id" => customization_id,
        "language_customization_id" => language_customization_id,
        "acoustic_customization_id" => acoustic_customization_id,
        "customization_weight" => customization_weight,
        "base_model_version" => base_model_version
      }
      params.delete_if { |_, v| v.nil? }
      service_url += "/v1/recognize?" + HTTP::URI.form_encode(params)
      options = {
        "content_type" => content_type,
        "inactivity_timeout" => inactivity_timeout,
        "interim_results" => interim_results,
        "keywords" => keywords,
        "keywords_threshold" => keywords_threshold,
        "max_alternatives" => max_alternatives,
        "word_alternatives_threshold" => word_alternatives_threshold,
        "word_confidence" => word_confidence,
        "timestamps" => timestamps,
        "profanity_filter" => profanity_filter,
        "smart_formatting" => smart_formatting,
        "speaker_labels" => speaker_labels,
        "grammar_name" => grammar_name,
        "redaction" => redaction,
        "processing_metrics" => processing_metrics,
        "processing_metrics_interval" => processing_metrics_interval,
        "audio_metrics" => audio_metrics,
        "end_of_phrase_silence_time" => end_of_phrase_silence_time,
        "split_transcript_at_phrase_end" => split_transcript_at_phrase_end,
        "speech_detector_sensitivity" => speech_detector_sensitivity,
        "background_audio_suppression" => background_audio_suppression,
        "low_latency" => low_latency
      }
      options.delete_if { |_, v| v.nil? }
      WebSocketClient.new(audio: audio, chunk_data: chunk_data, options: options, recognize_callback: recognize_callback, service_url: service_url, headers: headers, disable_ssl_verification: @disable_ssl_verification)
    end

    #########################
    # Asynchronous
    #########################

    ##
    # @!method register_callback(callback_url:, user_secret: nil)
    # Register a callback.
    # Registers a callback URL with the service for use with subsequent asynchronous
    #   recognition requests. The service attempts to register, or allowlist, the callback
    #   URL if it is not already registered by sending a `GET` request to the callback
    #   URL. The service passes a random alphanumeric challenge string via the
    #   `challenge_string` parameter of the request. The request includes an `Accept`
    #   header that specifies `text/plain` as the required response type.
    #
    #   To be registered successfully, the callback URL must respond to the `GET` request
    #   from the service. The response must send status code 200 and must include the
    #   challenge string in its body. Set the `Content-Type` response header to
    #   `text/plain`. Upon receiving this response, the service responds to the original
    #   registration request with response code 201.
    #
    #   The service sends only a single `GET` request to the callback URL. If the service
    #   does not receive a reply with a response code of 200 and a body that echoes the
    #   challenge string sent by the service within five seconds, it does not allowlist
    #   the URL; it instead sends status code 400 in response to the request to register a
    #   callback. If the requested callback URL is already allowlisted, the service
    #   responds to the initial registration request with response code 200.
    #
    #   If you specify a user secret with the request, the service uses it as a key to
    #   calculate an HMAC-SHA1 signature of the challenge string in its response to the
    #   `POST` request. It sends this signature in the `X-Callback-Signature` header of
    #   its `GET` request to the URL during registration. It also uses the secret to
    #   calculate a signature over the payload of every callback notification that uses
    #   the URL. The signature provides authentication and data integrity for HTTP
    #   communications.
    #
    #   After you successfully register a callback URL, you can use it with an indefinite
    #   number of recognition requests. You can register a maximum of 20 callback URLS in
    #   a one-hour span of time.
    #
    #   **See also:** [Registering a callback
    #   URL](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-async#register).
    # @param callback_url [String] An HTTP or HTTPS URL to which callback notifications are to be sent. To be
    #   allowlisted, the URL must successfully echo the challenge string during URL
    #   verification. During verification, the client can also check the signature that
    #   the service sends in the `X-Callback-Signature` header to verify the origin of the
    #   request.
    # @param user_secret [String] A user-specified string that the service uses to generate the HMAC-SHA1 signature
    #   that it sends via the `X-Callback-Signature` header. The service includes the
    #   header during URL verification and with every notification sent to the callback
    #   URL. It calculates the signature over the payload of the notification. If you omit
    #   the parameter, the service does not send the header.
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def register_callback(callback_url:, user_secret: nil)
      raise ArgumentError.new("callback_url must be provided") if callback_url.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "register_callback")
      headers.merge!(sdk_headers)

      params = {
        "callback_url" => callback_url,
        "user_secret" => user_secret
      }

      method_url = "/v1/register_callback"

      response = request(
        method: "POST",
        url: method_url,
        headers: headers,
        params: params,
        accept_json: true
      )
      response
    end

    ##
    # @!method unregister_callback(callback_url:)
    # Unregister a callback.
    # Unregisters a callback URL that was previously allowlisted with a [Register a
    #   callback](#registercallback) request for use with the asynchronous interface. Once
    #   unregistered, the URL can no longer be used with asynchronous recognition
    #   requests.
    #
    #   **See also:** [Unregistering a callback
    #   URL](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-async#unregister).
    # @param callback_url [String] The callback URL that is to be unregistered.
    # @return [nil]
    def unregister_callback(callback_url:)
      raise ArgumentError.new("callback_url must be provided") if callback_url.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "unregister_callback")
      headers.merge!(sdk_headers)

      params = {
        "callback_url" => callback_url
      }

      method_url = "/v1/unregister_callback"

      request(
        method: "POST",
        url: method_url,
        headers: headers,
        params: params,
        accept_json: false
      )
      nil
    end

    ##
    # @!method create_job(audio:, content_type: nil, model: nil, callback_url: nil, events: nil, user_token: nil, results_ttl: nil, language_customization_id: nil, acoustic_customization_id: nil, base_model_version: nil, customization_weight: nil, inactivity_timeout: nil, keywords: nil, keywords_threshold: nil, max_alternatives: nil, word_alternatives_threshold: nil, word_confidence: nil, timestamps: nil, profanity_filter: nil, smart_formatting: nil, speaker_labels: nil, customization_id: nil, grammar_name: nil, redaction: nil, processing_metrics: nil, processing_metrics_interval: nil, audio_metrics: nil, end_of_phrase_silence_time: nil, split_transcript_at_phrase_end: nil, speech_detector_sensitivity: nil, background_audio_suppression: nil, low_latency: nil)
    # Create a job.
    # Creates a job for a new asynchronous recognition request. The job is owned by the
    #   instance of the service whose credentials are used to create it. How you learn the
    #   status and results of a job depends on the parameters you include with the job
    #   creation request:
    #   * By callback notification: Include the `callback_url` parameter to specify a URL
    #   to which the service is to send callback notifications when the status of the job
    #   changes. Optionally, you can also include the `events` and `user_token` parameters
    #   to subscribe to specific events and to specify a string that is to be included
    #   with each notification for the job.
    #   * By polling the service: Omit the `callback_url`, `events`, and `user_token`
    #   parameters. You must then use the [Check jobs](#checkjobs) or [Check a
    #   job](#checkjob) methods to check the status of the job, using the latter to
    #   retrieve the results when the job is complete.
    #
    #   The two approaches are not mutually exclusive. You can poll the service for job
    #   status or obtain results from the service manually even if you include a callback
    #   URL. In both cases, you can include the `results_ttl` parameter to specify how
    #   long the results are to remain available after the job is complete. Using the
    #   HTTPS [Check a job](#checkjob) method to retrieve results is more secure than
    #   receiving them via callback notification over HTTP because it provides
    #   confidentiality in addition to authentication and data integrity.
    #
    #   The method supports the same basic parameters as other HTTP and WebSocket
    #   recognition requests. It also supports the following parameters specific to the
    #   asynchronous interface:
    #   * `callback_url`
    #   * `events`
    #   * `user_token`
    #   * `results_ttl`
    #
    #   You can pass a maximum of 1 GB and a minimum of 100 bytes of audio with a request.
    #   The service automatically detects the endianness of the incoming audio and, for
    #   audio that includes multiple channels, downmixes the audio to one-channel mono
    #   during transcoding. The method returns only final results; to enable interim
    #   results, use the WebSocket API. (With the `curl` command, use the `--data-binary`
    #   option to upload the file for the request.)
    #
    #   **See also:** [Creating a
    #   job](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-async#create).
    #
    #
    #   ### Streaming mode
    #
    #    For requests to transcribe live audio as it becomes available, you must set the
    #   `Transfer-Encoding` header to `chunked` to use streaming mode. In streaming mode,
    #   the service closes the connection (status code 408) if it does not receive at
    #   least 15 seconds of audio (including silence) in any 30-second period. The service
    #   also closes the connection (status code 400) if it detects no speech for
    #   `inactivity_timeout` seconds of streaming audio; use the `inactivity_timeout`
    #   parameter to change the default of 30 seconds.
    #
    #   **See also:**
    #   * [Audio
    #   transmission](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-input#transmission)
    #   *
    #   [Timeouts](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-input#timeouts)
    #
    #
    #   ### Audio formats (content types)
    #
    #    The service accepts audio in the following formats (MIME types).
    #   * For formats that are labeled **Required**, you must use the `Content-Type`
    #   header with the request to specify the format of the audio.
    #   * For all other formats, you can omit the `Content-Type` header or specify
    #   `application/octet-stream` with the header to have the service automatically
    #   detect the format of the audio. (With the `curl` command, you can specify either
    #   `"Content-Type:"` or `"Content-Type: application/octet-stream"`.)
    #
    #   Where indicated, the format that you specify must include the sampling rate and
    #   can optionally include the number of channels and the endianness of the audio.
    #   * `audio/alaw` (**Required.** Specify the sampling rate (`rate`) of the audio.)
    #   * `audio/basic` (**Required.** Use only with narrowband models.)
    #   * `audio/flac`
    #   * `audio/g729` (Use only with narrowband models.)
    #   * `audio/l16` (**Required.** Specify the sampling rate (`rate`) and optionally the
    #   number of channels (`channels`) and endianness (`endianness`) of the audio.)
    #   * `audio/mp3`
    #   * `audio/mpeg`
    #   * `audio/mulaw` (**Required.** Specify the sampling rate (`rate`) of the audio.)
    #   * `audio/ogg` (The service automatically detects the codec of the input audio.)
    #   * `audio/ogg;codecs=opus`
    #   * `audio/ogg;codecs=vorbis`
    #   * `audio/wav` (Provide audio with a maximum of nine channels.)
    #   * `audio/webm` (The service automatically detects the codec of the input audio.)
    #   * `audio/webm;codecs=opus`
    #   * `audio/webm;codecs=vorbis`
    #
    #   The sampling rate of the audio must match the sampling rate of the model for the
    #   recognition request: for broadband models, at least 16 kHz; for narrowband models,
    #   at least 8 kHz. If the sampling rate of the audio is higher than the minimum
    #   required rate, the service down-samples the audio to the appropriate rate. If the
    #   sampling rate of the audio is lower than the minimum required rate, the request
    #   fails.
    #
    #    **See also:** [Supported audio
    #   formats](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-audio-formats).
    #
    #
    #   ### Next-generation models
    #
    #    The service supports next-generation `Multimedia` (16 kHz) and `Telephony` (8
    #   kHz) models for many languages. Next-generation models have higher throughput than
    #   the service's previous generation of `Broadband` and `Narrowband` models. When you
    #   use next-generation models, the service can return transcriptions more quickly and
    #   also provide noticeably better transcription accuracy.
    #
    #   You specify a next-generation model by using the `model` query parameter, as you
    #   do a previous-generation model. Many next-generation models also support the
    #   `low_latency` parameter, which is not available with previous-generation models.
    #   Next-generation models do not support all of the parameters that are available for
    #   use with previous-generation models.
    #
    #   **Important:** Effective 15 March 2022, previous-generation models for all
    #   languages other than Arabic and Japanese are deprecated. The deprecated models
    #   remain available until 15 September 2022, when they will be removed from the
    #   service and the documentation. You must migrate to the equivalent next-generation
    #   model by the end of service date. For more information, see  [Migrating to
    #   next-generation
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-migrate).
    #
    #
    #   **See also:**
    #   * [Next-generation languages and
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-ng)
    #   * [Supported features for next-generation
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-ng#models-ng-features).
    # @param audio [File] The audio to transcribe.
    # @param content_type [String] The format (MIME type) of the audio. For more information about specifying an
    #   audio format, see **Audio formats (content types)** in the method description.
    # @param model [String] The identifier of the model that is to be used for the recognition request.
    #   (**Note:** The model `ar-AR_BroadbandModel` is deprecated; use
    #   `ar-MS_BroadbandModel` instead.) See [Using a model for speech
    #   recognition](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-use).
    # @param callback_url [String] A URL to which callback notifications are to be sent. The URL must already be
    #   successfully allowlisted by using the [Register a callback](#registercallback)
    #   method. You can include the same callback URL with any number of job creation
    #   requests. Omit the parameter to poll the service for job completion and results.
    #
    #   Use the `user_token` parameter to specify a unique user-specified string with each
    #   job to differentiate the callback notifications for the jobs.
    # @param events [String] If the job includes a callback URL, a comma-separated list of notification events
    #   to which to subscribe. Valid events are
    #   * `recognitions.started` generates a callback notification when the service begins
    #   to process the job.
    #   * `recognitions.completed` generates a callback notification when the job is
    #   complete. You must use the [Check a job](#checkjob) method to retrieve the results
    #   before they time out or are deleted.
    #   * `recognitions.completed_with_results` generates a callback notification when the
    #   job is complete. The notification includes the results of the request.
    #   * `recognitions.failed` generates a callback notification if the service
    #   experiences an error while processing the job.
    #
    #   The `recognitions.completed` and `recognitions.completed_with_results` events are
    #   incompatible. You can specify only of the two events.
    #
    #   If the job includes a callback URL, omit the parameter to subscribe to the default
    #   events: `recognitions.started`, `recognitions.completed`, and
    #   `recognitions.failed`. If the job does not include a callback URL, omit the
    #   parameter.
    # @param user_token [String] If the job includes a callback URL, a user-specified string that the service is to
    #   include with each callback notification for the job; the token allows the user to
    #   maintain an internal mapping between jobs and notification events. If the job does
    #   not include a callback URL, omit the parameter.
    # @param results_ttl [Fixnum] The number of minutes for which the results are to be available after the job has
    #   finished. If not delivered via a callback, the results must be retrieved within
    #   this time. Omit the parameter to use a time to live of one week. The parameter is
    #   valid with or without a callback URL.
    # @param language_customization_id [String] The customization ID (GUID) of a custom language model that is to be used with the
    #   recognition request. The base model of the specified custom language model must
    #   match the model specified with the `model` parameter. You must make the request
    #   with credentials for the instance of the service that owns the custom model. By
    #   default, no custom language model is used. See [Using a custom language model for
    #   speech
    #   recognition](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-languageUse).
    #
    #
    #   **Note:** Use this parameter instead of the deprecated `customization_id`
    #   parameter.
    # @param acoustic_customization_id [String] The customization ID (GUID) of a custom acoustic model that is to be used with the
    #   recognition request. The base model of the specified custom acoustic model must
    #   match the model specified with the `model` parameter. You must make the request
    #   with credentials for the instance of the service that owns the custom model. By
    #   default, no custom acoustic model is used. See [Using a custom acoustic model for
    #   speech
    #   recognition](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-acousticUse).
    # @param base_model_version [String] The version of the specified base model that is to be used with the recognition
    #   request. Multiple versions of a base model can exist when a model is updated for
    #   internal improvements. The parameter is intended primarily for use with custom
    #   models that have been upgraded for a new base model. The default value depends on
    #   whether the parameter is used with or without a custom model. See [Making speech
    #   recognition requests with upgraded custom
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-upgrade-use#custom-upgrade-use-recognition).
    # @param customization_weight [Float] If you specify the customization ID (GUID) of a custom language model with the
    #   recognition request, the customization weight tells the service how much weight to
    #   give to words from the custom language model compared to those from the base model
    #   for the current request.
    #
    #   Specify a value between 0.0 and 1.0. Unless a different customization weight was
    #   specified for the custom model when it was trained, the default value is 0.3. A
    #   customization weight that you specify overrides a weight that was specified when
    #   the custom model was trained.
    #
    #   The default value yields the best performance in general. Assign a higher value if
    #   your audio makes frequent use of OOV words from the custom model. Use caution when
    #   setting the weight: a higher value can improve the accuracy of phrases from the
    #   custom model's domain, but it can negatively affect performance on non-domain
    #   phrases.
    #
    #   See [Using customization
    #   weight](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-languageUse#weight).
    # @param inactivity_timeout [Fixnum] The time in seconds after which, if only silence (no speech) is detected in
    #   streaming audio, the connection is closed with a 400 error. The parameter is
    #   useful for stopping audio submission from a live microphone when a user simply
    #   walks away. Use `-1` for infinity. See [Inactivity
    #   timeout](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-input#timeouts-inactivity).
    # @param keywords [Array[String]] An array of keyword strings to spot in the audio. Each keyword string can include
    #   one or more string tokens. Keywords are spotted only in the final results, not in
    #   interim hypotheses. If you specify any keywords, you must also specify a keywords
    #   threshold. Omit the parameter or specify an empty array if you do not need to spot
    #   keywords.
    #
    #   You can spot a maximum of 1000 keywords with a single request. A single keyword
    #   can have a maximum length of 1024 characters, though the maximum effective length
    #   for double-byte languages might be shorter. Keywords are case-insensitive.
    #
    #   See [Keyword
    #   spotting](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-spotting#keyword-spotting).
    # @param keywords_threshold [Float] A confidence value that is the lower bound for spotting a keyword. A word is
    #   considered to match a keyword if its confidence is greater than or equal to the
    #   threshold. Specify a probability between 0.0 and 1.0. If you specify a threshold,
    #   you must also specify one or more keywords. The service performs no keyword
    #   spotting if you omit either parameter. See [Keyword
    #   spotting](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-spotting#keyword-spotting).
    # @param max_alternatives [Fixnum] The maximum number of alternative transcripts that the service is to return. By
    #   default, the service returns a single transcript. If you specify a value of `0`,
    #   the service uses the default value, `1`. See [Maximum
    #   alternatives](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-metadata#max-alternatives).
    # @param word_alternatives_threshold [Float] A confidence value that is the lower bound for identifying a hypothesis as a
    #   possible word alternative (also known as "Confusion Networks"). An alternative
    #   word is considered if its confidence is greater than or equal to the threshold.
    #   Specify a probability between 0.0 and 1.0. By default, the service computes no
    #   alternative words. See [Word
    #   alternatives](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-spotting#word-alternatives).
    # @param word_confidence [Boolean] If `true`, the service returns a confidence measure in the range of 0.0 to 1.0 for
    #   each word. By default, the service returns no word confidence scores. See [Word
    #   confidence](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-metadata#word-confidence).
    # @param timestamps [Boolean] If `true`, the service returns time alignment for each word. By default, no
    #   timestamps are returned. See [Word
    #   timestamps](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-metadata#word-timestamps).
    # @param profanity_filter [Boolean] If `true`, the service filters profanity from all output except for keyword
    #   results by replacing inappropriate words with a series of asterisks. Set the
    #   parameter to `false` to return results with no censoring.
    #
    #   **Note:** The parameter can be used with US English and Japanese transcription
    #   only. See [Profanity
    #   filtering](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-formatting#profanity-filtering).
    # @param smart_formatting [Boolean] If `true`, the service converts dates, times, series of digits and numbers, phone
    #   numbers, currency values, and internet addresses into more readable, conventional
    #   representations in the final transcript of a recognition request. For US English,
    #   the service also converts certain keyword strings to punctuation symbols. By
    #   default, the service performs no smart formatting.
    #
    #   **Note:** The parameter can be used with US English, Japanese, and Spanish (all
    #   dialects) transcription only.
    #
    #   See [Smart
    #   formatting](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-formatting#smart-formatting).
    # @param speaker_labels [Boolean] If `true`, the response includes labels that identify which words were spoken by
    #   which participants in a multi-person exchange. By default, the service returns no
    #   speaker labels. Setting `speaker_labels` to `true` forces the `timestamps`
    #   parameter to be `true`, regardless of whether you specify `false` for the
    #   parameter.
    #   * _For previous-generation models,_ the parameter can be used with Australian
    #   English, US English, German, Japanese, Korean, and Spanish (both broadband and
    #   narrowband models) and UK English (narrowband model) transcription only.
    #   * _For next-generation models,_ the parameter can be used with Czech, English
    #   (Australian, Indian, UK, and US), German, Japanese, Korean, and Spanish
    #   transcription only.
    #
    #   See [Speaker
    #   labels](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-speaker-labels).
    # @param customization_id [String] **Deprecated.** Use the `language_customization_id` parameter to specify the
    #   customization ID (GUID) of a custom language model that is to be used with the
    #   recognition request. Do not specify both parameters with a request.
    # @param grammar_name [String] The name of a grammar that is to be used with the recognition request. If you
    #   specify a grammar, you must also use the `language_customization_id` parameter to
    #   specify the name of the custom language model for which the grammar is defined.
    #   The service recognizes only strings that are recognized by the specified grammar;
    #   it does not recognize other custom words from the model's words resource.
    #
    #   See [Using a grammar for speech
    #   recognition](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-grammarUse).
    # @param redaction [Boolean] If `true`, the service redacts, or masks, numeric data from final transcripts. The
    #   feature redacts any number that has three or more consecutive digits by replacing
    #   each digit with an `X` character. It is intended to redact sensitive numeric data,
    #   such as credit card numbers. By default, the service performs no redaction.
    #
    #   When you enable redaction, the service automatically enables smart formatting,
    #   regardless of whether you explicitly disable that feature. To ensure maximum
    #   security, the service also disables keyword spotting (ignores the `keywords` and
    #   `keywords_threshold` parameters) and returns only a single final transcript
    #   (forces the `max_alternatives` parameter to be `1`).
    #
    #   **Note:** The parameter can be used with US English, Japanese, and Korean
    #   transcription only.
    #
    #   See [Numeric
    #   redaction](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-formatting#numeric-redaction).
    # @param processing_metrics [Boolean] If `true`, requests processing metrics about the service's transcription of the
    #   input audio. The service returns processing metrics at the interval specified by
    #   the `processing_metrics_interval` parameter. It also returns processing metrics
    #   for transcription events, for example, for final and interim results. By default,
    #   the service returns no processing metrics.
    #
    #   See [Processing
    #   metrics](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-metrics#processing-metrics).
    # @param processing_metrics_interval [Float] Specifies the interval in real wall-clock seconds at which the service is to
    #   return processing metrics. The parameter is ignored unless the
    #   `processing_metrics` parameter is set to `true`.
    #
    #   The parameter accepts a minimum value of 0.1 seconds. The level of precision is
    #   not restricted, so you can specify values such as 0.25 and 0.125.
    #
    #   The service does not impose a maximum value. If you want to receive processing
    #   metrics only for transcription events instead of at periodic intervals, set the
    #   value to a large number. If the value is larger than the duration of the audio,
    #   the service returns processing metrics only for transcription events.
    #
    #   See [Processing
    #   metrics](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-metrics#processing-metrics).
    # @param audio_metrics [Boolean] If `true`, requests detailed information about the signal characteristics of the
    #   input audio. The service returns audio metrics with the final transcription
    #   results. By default, the service returns no audio metrics.
    #
    #   See [Audio
    #   metrics](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-metrics#audio-metrics).
    # @param end_of_phrase_silence_time [Float] If `true`, specifies the duration of the pause interval at which the service
    #   splits a transcript into multiple final results. If the service detects pauses or
    #   extended silence before it reaches the end of the audio stream, its response can
    #   include multiple final results. Silence indicates a point at which the speaker
    #   pauses between spoken words or phrases.
    #
    #   Specify a value for the pause interval in the range of 0.0 to 120.0.
    #   * A value greater than 0 specifies the interval that the service is to use for
    #   speech recognition.
    #   * A value of 0 indicates that the service is to use the default interval. It is
    #   equivalent to omitting the parameter.
    #
    #   The default pause interval for most languages is 0.8 seconds; the default for
    #   Chinese is 0.6 seconds.
    #
    #   See [End of phrase silence
    #   time](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-parsing#silence-time).
    # @param split_transcript_at_phrase_end [Boolean] If `true`, directs the service to split the transcript into multiple final results
    #   based on semantic features of the input, for example, at the conclusion of
    #   meaningful phrases such as sentences. The service bases its understanding of
    #   semantic features on the base language model that you use with a request. Custom
    #   language models and grammars can also influence how and where the service splits a
    #   transcript.
    #
    #   By default, the service splits transcripts based solely on the pause interval. If
    #   the parameters are used together on the same request, `end_of_phrase_silence_time`
    #   has precedence over `split_transcript_at_phrase_end`.
    #
    #   See [Split transcript at phrase
    #   end](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-parsing#split-transcript).
    # @param speech_detector_sensitivity [Float] The sensitivity of speech activity detection that the service is to perform. Use
    #   the parameter to suppress word insertions from music, coughing, and other
    #   non-speech events. The service biases the audio it passes for speech recognition
    #   by evaluating the input audio against prior models of speech and non-speech
    #   activity.
    #
    #   Specify a value between 0.0 and 1.0:
    #   * 0.0 suppresses all audio (no speech is transcribed).
    #   * 0.5 (the default) provides a reasonable compromise for the level of sensitivity.
    #   * 1.0 suppresses no audio (speech detection sensitivity is disabled).
    #
    #   The values increase on a monotonic curve.
    #
    #   The parameter is supported with all next-generation models and with most
    #   previous-generation models. See [Speech detector
    #   sensitivity](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-detection#detection-parameters-sensitivity)
    #   and [Language model
    #   support](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-detection#detection-support).
    # @param background_audio_suppression [Float] The level to which the service is to suppress background audio based on its volume
    #   to prevent it from being transcribed as speech. Use the parameter to suppress side
    #   conversations or background noise.
    #
    #   Specify a value in the range of 0.0 to 1.0:
    #   * 0.0 (the default) provides no suppression (background audio suppression is
    #   disabled).
    #   * 0.5 provides a reasonable level of audio suppression for general usage.
    #   * 1.0 suppresses all audio (no audio is transcribed).
    #
    #   The values increase on a monotonic curve.
    #
    #   The parameter is supported with all next-generation models and with most
    #   previous-generation models. See [Background audio
    #   suppression](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-detection#detection-parameters-suppression)
    #   and [Language model
    #   support](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-detection#detection-support).
    # @param low_latency [Boolean] If `true` for next-generation `Multimedia` and `Telephony` models that support low
    #   latency, directs the service to produce results even more quickly than it usually
    #   does. Next-generation models produce transcription results faster than
    #   previous-generation models. The `low_latency` parameter causes the models to
    #   produce results even more quickly, though the results might be less accurate when
    #   the parameter is used.
    #
    #   The parameter is not available for previous-generation `Broadband` and
    #   `Narrowband` models. It is available only for some next-generation models. For a
    #   list of next-generation models that support low latency, see [Supported
    #   next-generation language
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-ng#models-ng-supported).
    #   * For more information about the `low_latency` parameter, see [Low
    #   latency](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-interim#low-latency).
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def create_job(audio:, content_type: nil, model: nil, callback_url: nil, events: nil, user_token: nil, results_ttl: nil, language_customization_id: nil, acoustic_customization_id: nil, base_model_version: nil, customization_weight: nil, inactivity_timeout: nil, keywords: nil, keywords_threshold: nil, max_alternatives: nil, word_alternatives_threshold: nil, word_confidence: nil, timestamps: nil, profanity_filter: nil, smart_formatting: nil, speaker_labels: nil, customization_id: nil, grammar_name: nil, redaction: nil, processing_metrics: nil, processing_metrics_interval: nil, audio_metrics: nil, end_of_phrase_silence_time: nil, split_transcript_at_phrase_end: nil, speech_detector_sensitivity: nil, background_audio_suppression: nil, low_latency: nil)
      raise ArgumentError.new("audio must be provided") if audio.nil?

      headers = {
        "Content-Type" => content_type
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "create_job")
      headers.merge!(sdk_headers)
      keywords *= "," unless keywords.nil?

      params = {
        "model" => model,
        "callback_url" => callback_url,
        "events" => events,
        "user_token" => user_token,
        "results_ttl" => results_ttl,
        "language_customization_id" => language_customization_id,
        "acoustic_customization_id" => acoustic_customization_id,
        "base_model_version" => base_model_version,
        "customization_weight" => customization_weight,
        "inactivity_timeout" => inactivity_timeout,
        "keywords" => keywords,
        "keywords_threshold" => keywords_threshold,
        "max_alternatives" => max_alternatives,
        "word_alternatives_threshold" => word_alternatives_threshold,
        "word_confidence" => word_confidence,
        "timestamps" => timestamps,
        "profanity_filter" => profanity_filter,
        "smart_formatting" => smart_formatting,
        "speaker_labels" => speaker_labels,
        "customization_id" => customization_id,
        "grammar_name" => grammar_name,
        "redaction" => redaction,
        "processing_metrics" => processing_metrics,
        "processing_metrics_interval" => processing_metrics_interval,
        "audio_metrics" => audio_metrics,
        "end_of_phrase_silence_time" => end_of_phrase_silence_time,
        "split_transcript_at_phrase_end" => split_transcript_at_phrase_end,
        "speech_detector_sensitivity" => speech_detector_sensitivity,
        "background_audio_suppression" => background_audio_suppression,
        "low_latency" => low_latency
      }

      data = audio

      method_url = "/v1/recognitions"

      response = request(
        method: "POST",
        url: method_url,
        headers: headers,
        params: params,
        data: data,
        accept_json: true
      )
      response
    end

    ##
    # @!method check_jobs
    # Check jobs.
    # Returns the ID and status of the latest 100 outstanding jobs associated with the
    #   credentials with which it is called. The method also returns the creation and
    #   update times of each job, and, if a job was created with a callback URL and a user
    #   token, the user token for the job. To obtain the results for a job whose status is
    #   `completed` or not one of the latest 100 outstanding jobs, use the [Check a
    #   job[(#checkjob) method. A job and its results remain available until you delete
    #   them with the [Delete a job](#deletejob) method or until the job's time to live
    #   expires, whichever comes first.
    #
    #   **See also:** [Checking the status of the latest
    #   jobs](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-async#jobs).
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def check_jobs
      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "check_jobs")
      headers.merge!(sdk_headers)

      method_url = "/v1/recognitions"

      response = request(
        method: "GET",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      response
    end

    ##
    # @!method check_job(id:)
    # Check a job.
    # Returns information about the specified job. The response always includes the
    #   status of the job and its creation and update times. If the status is `completed`,
    #   the response includes the results of the recognition request. You must use
    #   credentials for the instance of the service that owns a job to list information
    #   about it.
    #
    #   You can use the method to retrieve the results of any job, regardless of whether
    #   it was submitted with a callback URL and the `recognitions.completed_with_results`
    #   event, and you can retrieve the results multiple times for as long as they remain
    #   available. Use the [Check jobs](#checkjobs) method to request information about
    #   the most recent jobs associated with the calling credentials.
    #
    #   **See also:** [Checking the status and retrieving the results of a
    #   job](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-async#job).
    # @param id [String] The identifier of the asynchronous job that is to be used for the request. You
    #   must make the request with credentials for the instance of the service that owns
    #   the job.
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def check_job(id:)
      raise ArgumentError.new("id must be provided") if id.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "check_job")
      headers.merge!(sdk_headers)

      method_url = "/v1/recognitions/%s" % [ERB::Util.url_encode(id)]

      response = request(
        method: "GET",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      response
    end

    ##
    # @!method delete_job(id:)
    # Delete a job.
    # Deletes the specified job. You cannot delete a job that the service is actively
    #   processing. Once you delete a job, its results are no longer available. The
    #   service automatically deletes a job and its results when the time to live for the
    #   results expires. You must use credentials for the instance of the service that
    #   owns a job to delete it.
    #
    #   **See also:** [Deleting a
    #   job](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-async#delete-async).
    # @param id [String] The identifier of the asynchronous job that is to be used for the request. You
    #   must make the request with credentials for the instance of the service that owns
    #   the job.
    # @return [nil]
    def delete_job(id:)
      raise ArgumentError.new("id must be provided") if id.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "delete_job")
      headers.merge!(sdk_headers)

      method_url = "/v1/recognitions/%s" % [ERB::Util.url_encode(id)]

      request(
        method: "DELETE",
        url: method_url,
        headers: headers,
        accept_json: false
      )
      nil
    end
    #########################
    # Custom language models
    #########################

    ##
    # @!method create_language_model(name:, base_model_name:, dialect: nil, description: nil)
    # Create a custom language model.
    # Creates a new custom language model for a specified base model. The custom
    #   language model can be used only with the base model for which it is created. The
    #   model is owned by the instance of the service whose credentials are used to create
    #   it.
    #
    #   You can create a maximum of 1024 custom language models per owning credentials.
    #   The service returns an error if you attempt to create more than 1024 models. You
    #   do not lose any models, but you cannot create any more until your model count is
    #   below the limit.
    #
    #   **Important:** Effective 15 March 2022, previous-generation models for all
    #   languages other than Arabic and Japanese are deprecated. The deprecated models
    #   remain available until 15 September 2022, when they will be removed from the
    #   service and the documentation. You must migrate to the equivalent next-generation
    #   model by the end of service date. For more information, see [Migrating to
    #   next-generation
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-migrate).
    #
    #
    #   **See also:**
    #   * [Create a custom language
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-languageCreate#createModel-language)
    #   * [Language support for
    #   customization](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-support).
    # @param name [String] A user-defined name for the new custom language model. Use a name that is unique
    #   among all custom language models that you own. Use a localized name that matches
    #   the language of the custom model. Use a name that describes the domain of the
    #   custom model, such as `Medical custom model` or `Legal custom model`.
    # @param base_model_name [String] The name of the base language model that is to be customized by the new custom
    #   language model. The new custom model can be used only with the base model that it
    #   customizes.
    #
    #   To determine whether a base model supports language model customization, use the
    #   [Get a model](#getmodel) method and check that the attribute
    #   `custom_language_model` is set to `true`. You can also refer to [Language support
    #   for
    #   customization](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-support).
    # @param dialect [String] The dialect of the specified language that is to be used with the custom language
    #   model. _For all languages, it is always safe to omit this field._ The service
    #   automatically uses the language identifier from the name of the base model. For
    #   example, the service automatically uses `en-US` for all US English models.
    #
    #   If you specify the `dialect` for a new custom model, follow these guidelines. _For
    #   non-Spanish previous-generation models and for next-generation models,_ you must
    #   specify a value that matches the five-character language identifier from the name
    #   of the base model. _For Spanish previous-generation models,_ you must specify one
    #   of the following values:
    #   * `es-ES` for Castilian Spanish (`es-ES` models)
    #   * `es-LA` for Latin American Spanish (`es-AR`, `es-CL`, `es-CO`, and `es-PE`
    #   models)
    #   * `es-US` for Mexican (North American) Spanish (`es-MX` models)
    #
    #   All values that you pass for the `dialect` field are case-insensitive.
    # @param description [String] A description of the new custom language model. Use a localized description that
    #   matches the language of the custom model.
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def create_language_model(name:, base_model_name:, dialect: nil, description: nil)
      raise ArgumentError.new("name must be provided") if name.nil?

      raise ArgumentError.new("base_model_name must be provided") if base_model_name.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "create_language_model")
      headers.merge!(sdk_headers)

      data = {
        "name" => name,
        "base_model_name" => base_model_name,
        "dialect" => dialect,
        "description" => description
      }

      method_url = "/v1/customizations"

      response = request(
        method: "POST",
        url: method_url,
        headers: headers,
        json: data,
        accept_json: true
      )
      response
    end

    ##
    # @!method list_language_models(language: nil)
    # List custom language models.
    # Lists information about all custom language models that are owned by an instance
    #   of the service. Use the `language` parameter to see all custom language models for
    #   the specified language. Omit the parameter to see all custom language models for
    #   all languages. You must use credentials for the instance of the service that owns
    #   a model to list information about it.
    #
    #   **See also:**
    #   * [Listing custom language
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageLanguageModels#listModels-language)
    #   * [Language support for
    #   customization](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-support).
    # @param language [String] The identifier of the language for which custom language or custom acoustic models
    #   are to be returned. Specify the five-character language identifier; for example,
    #   specify `en-US` to see all custom language or custom acoustic models that are
    #   based on US English models. Omit the parameter to see all custom language or
    #   custom acoustic models that are owned by the requesting credentials. (**Note:**
    #   The identifier `ar-AR` is deprecated; use `ar-MS` instead.)
    #
    #   To determine the languages for which customization is available, see [Language
    #   support for
    #   customization](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-support).
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def list_language_models(language: nil)
      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "list_language_models")
      headers.merge!(sdk_headers)

      params = {
        "language" => language
      }

      method_url = "/v1/customizations"

      response = request(
        method: "GET",
        url: method_url,
        headers: headers,
        params: params,
        accept_json: true
      )
      response
    end

    ##
    # @!method get_language_model(customization_id:)
    # Get a custom language model.
    # Gets information about a specified custom language model. You must use credentials
    #   for the instance of the service that owns a model to list information about it.
    #
    #   **See also:**
    #   * [Listing custom language
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageLanguageModels#listModels-language)
    #   * [Language support for
    #   customization](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-support).
    # @param customization_id [String] The customization ID (GUID) of the custom language model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def get_language_model(customization_id:)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "get_language_model")
      headers.merge!(sdk_headers)

      method_url = "/v1/customizations/%s" % [ERB::Util.url_encode(customization_id)]

      response = request(
        method: "GET",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      response
    end

    ##
    # @!method delete_language_model(customization_id:)
    # Delete a custom language model.
    # Deletes an existing custom language model. The custom model cannot be deleted if
    #   another request, such as adding a corpus or grammar to the model, is currently
    #   being processed. You must use credentials for the instance of the service that
    #   owns a model to delete it.
    #
    #   **See also:**
    #   * [Deleting a custom language
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageLanguageModels#deleteModel-language)
    #   * [Language support for
    #   customization](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-support).
    # @param customization_id [String] The customization ID (GUID) of the custom language model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @return [nil]
    def delete_language_model(customization_id:)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "delete_language_model")
      headers.merge!(sdk_headers)

      method_url = "/v1/customizations/%s" % [ERB::Util.url_encode(customization_id)]

      request(
        method: "DELETE",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      nil
    end

    ##
    # @!method train_language_model(customization_id:, word_type_to_add: nil, customization_weight: nil)
    # Train a custom language model.
    # Initiates the training of a custom language model with new resources such as
    #   corpora, grammars, and custom words. After adding, modifying, or deleting
    #   resources for a custom language model, use this method to begin the actual
    #   training of the model on the latest data. You can specify whether the custom
    #   language model is to be trained with all words from its words resource or only
    #   with words that were added or modified by the user directly. You must use
    #   credentials for the instance of the service that owns a model to train it.
    #
    #   The training method is asynchronous. It can take on the order of minutes to
    #   complete depending on the amount of data on which the service is being trained and
    #   the current load on the service. The method returns an HTTP 200 response code to
    #   indicate that the training process has begun.
    #
    #   You can monitor the status of the training by using the [Get a custom language
    #   model](#getlanguagemodel) method to poll the model's status. Use a loop to check
    #   the status every 10 seconds. The method returns a `LanguageModel` object that
    #   includes `status` and `progress` fields. A status of `available` means that the
    #   custom model is trained and ready to use. The service cannot accept subsequent
    #   training requests or requests to add new resources until the existing request
    #   completes.
    #
    #   **See also:**
    #   * [Train the custom language
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-languageCreate#trainModel-language)
    #   * [Language support for
    #   customization](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-support)
    #
    #
    #   ### Training failures
    #
    #    Training can fail to start for the following reasons:
    #   * The service is currently handling another request for the custom model, such as
    #   another training request or a request to add a corpus or grammar to the model.
    #   * No training data have been added to the custom model.
    #   * The custom model contains one or more invalid corpora, grammars, or words (for
    #   example, a custom word has an invalid sounds-like pronunciation). You can correct
    #   the invalid resources or set the `strict` parameter to `false` to exclude the
    #   invalid resources from the training. The model must contain at least one valid
    #   resource for training to succeed.
    # @param customization_id [String] The customization ID (GUID) of the custom language model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @param word_type_to_add [String] _For custom models that are based on previous-generation models_, the type of
    #   words from the custom language model's words resource on which to train the model:
    #   * `all` (the default) trains the model on all new words, regardless of whether
    #   they were extracted from corpora or grammars or were added or modified by the
    #   user.
    #   * `user` trains the model only on custom words that were added or modified by the
    #   user directly. The model is not trained on new words extracted from corpora or
    #   grammars.
    #
    #   _For custom models that are based on next-generation models_, the service ignores
    #   the parameter. The words resource contains only custom words that the user adds or
    #   modifies directly, so the parameter is unnecessary.
    # @param customization_weight [Float] Specifies a customization weight for the custom language model. The customization
    #   weight tells the service how much weight to give to words from the custom language
    #   model compared to those from the base model for speech recognition. Specify a
    #   value between 0.0 and 1.0; the default is 0.3.
    #
    #   The default value yields the best performance in general. Assign a higher value if
    #   your audio makes frequent use of OOV words from the custom model. Use caution when
    #   setting the weight: a higher value can improve the accuracy of phrases from the
    #   custom model's domain, but it can negatively affect performance on non-domain
    #   phrases.
    #
    #   The value that you assign is used for all recognition requests that use the model.
    #   You can override it for any recognition request by specifying a customization
    #   weight for that request.
    #
    #   See [Using customization
    #   weight](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-languageUse#weight).
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def train_language_model(customization_id:, word_type_to_add: nil, customization_weight: nil)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "train_language_model")
      headers.merge!(sdk_headers)

      params = {
        "word_type_to_add" => word_type_to_add,
        "customization_weight" => customization_weight
      }

      method_url = "/v1/customizations/%s/train" % [ERB::Util.url_encode(customization_id)]

      response = request(
        method: "POST",
        url: method_url,
        headers: headers,
        params: params,
        accept_json: true
      )
      response
    end

    ##
    # @!method reset_language_model(customization_id:)
    # Reset a custom language model.
    # Resets a custom language model by removing all corpora, grammars, and words from
    #   the model. Resetting a custom language model initializes the model to its state
    #   when it was first created. Metadata such as the name and language of the model are
    #   preserved, but the model's words resource is removed and must be re-created. You
    #   must use credentials for the instance of the service that owns a model to reset
    #   it.
    #
    #   **See also:**
    #   * [Resetting a custom language
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageLanguageModels#resetModel-language)
    #   * [Language support for
    #   customization](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-support).
    # @param customization_id [String] The customization ID (GUID) of the custom language model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @return [nil]
    def reset_language_model(customization_id:)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "reset_language_model")
      headers.merge!(sdk_headers)

      method_url = "/v1/customizations/%s/reset" % [ERB::Util.url_encode(customization_id)]

      request(
        method: "POST",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      nil
    end

    ##
    # @!method upgrade_language_model(customization_id:)
    # Upgrade a custom language model.
    # Initiates the upgrade of a custom language model to the latest version of its base
    #   language model. The upgrade method is asynchronous. It can take on the order of
    #   minutes to complete depending on the amount of data in the custom model and the
    #   current load on the service. A custom model must be in the `ready` or `available`
    #   state to be upgraded. You must use credentials for the instance of the service
    #   that owns a model to upgrade it.
    #
    #   The method returns an HTTP 200 response code to indicate that the upgrade process
    #   has begun successfully. You can monitor the status of the upgrade by using the
    #   [Get a custom language model](#getlanguagemodel) method to poll the model's
    #   status. The method returns a `LanguageModel` object that includes `status` and
    #   `progress` fields. Use a loop to check the status every 10 seconds.
    #
    #   While it is being upgraded, the custom model has the status `upgrading`. When the
    #   upgrade is complete, the model resumes the status that it had prior to upgrade.
    #   The service cannot accept subsequent requests for the model until the upgrade
    #   completes.
    #
    #   **See also:**
    #   * [Upgrading a custom language
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-upgrade#custom-upgrade-language)
    #   * [Language support for
    #   customization](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-support).
    # @param customization_id [String] The customization ID (GUID) of the custom language model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @return [nil]
    def upgrade_language_model(customization_id:)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "upgrade_language_model")
      headers.merge!(sdk_headers)

      method_url = "/v1/customizations/%s/upgrade_model" % [ERB::Util.url_encode(customization_id)]

      request(
        method: "POST",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      nil
    end
    #########################
    # Custom corpora
    #########################

    ##
    # @!method list_corpora(customization_id:)
    # List corpora.
    # Lists information about all corpora from a custom language model. The information
    #   includes the name, status, and total number of words for each corpus. _For custom
    #   models that are based on previous-generation models_, it also includes the number
    #   of out-of-vocabulary (OOV) words from the corpus. You must use credentials for the
    #   instance of the service that owns a model to list its corpora.
    #
    #   **See also:** [Listing corpora for a custom language
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageCorpora#listCorpora).
    # @param customization_id [String] The customization ID (GUID) of the custom language model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def list_corpora(customization_id:)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "list_corpora")
      headers.merge!(sdk_headers)

      method_url = "/v1/customizations/%s/corpora" % [ERB::Util.url_encode(customization_id)]

      response = request(
        method: "GET",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      response
    end

    ##
    # @!method add_corpus(customization_id:, corpus_name:, corpus_file:, allow_overwrite: nil)
    # Add a corpus.
    # Adds a single corpus text file of new training data to a custom language model.
    #   Use multiple requests to submit multiple corpus text files. You must use
    #   credentials for the instance of the service that owns a model to add a corpus to
    #   it. Adding a corpus does not affect the custom language model until you train the
    #   model for the new data by using the [Train a custom language
    #   model](#trainlanguagemodel) method.
    #
    #   Submit a plain text file that contains sample sentences from the domain of
    #   interest to enable the service to parse the words in context. The more sentences
    #   you add that represent the context in which speakers use words from the domain,
    #   the better the service's recognition accuracy.
    #
    #   The call returns an HTTP 201 response code if the corpus is valid. The service
    #   then asynchronously processes and automatically extracts data from the contents of
    #   the corpus. This operation can take on the order of minutes to complete depending
    #   on the current load on the service, the total number of words in the corpus, and,
    #   _for custom models that are based on previous-generation models_, the number of
    #   new (out-of-vocabulary) words in the corpus. You cannot submit requests to add
    #   additional resources to the custom model or to train the model until the service's
    #   analysis of the corpus for the current request completes. Use the [Get a
    #   corpus](#getcorpus) method to check the status of the analysis.
    #
    #   _For custom models that are based on previous-generation models_, the service
    #   auto-populates the model's words resource with words from the corpus that are not
    #   found in its base vocabulary. These words are referred to as out-of-vocabulary
    #   (OOV) words. After adding a corpus, you must validate the words resource to ensure
    #   that each OOV word's definition is complete and valid. You can use the [List
    #   custom words](#listwords) method to examine the words resource. You can use other
    #   words method to eliminate typos and modify how words are pronounced as needed.
    #
    #   To add a corpus file that has the same name as an existing corpus, set the
    #   `allow_overwrite` parameter to `true`; otherwise, the request fails. Overwriting
    #   an existing corpus causes the service to process the corpus text file and extract
    #   its data anew. _For a custom model that is based on a previous-generation model_,
    #   the service first removes any OOV words that are associated with the existing
    #   corpus from the model's words resource unless they were also added by another
    #   corpus or grammar, or they have been modified in some way with the [Add custom
    #   words](#addwords) or [Add a custom word](#addword) method.
    #
    #   The service limits the overall amount of data that you can add to a custom model
    #   to a maximum of 10 million total words from all sources combined. _For a custom
    #   model that is based on a previous-generation model_, you can add no more than 90
    #   thousand custom (OOV) words to a model. This includes words that the service
    #   extracts from corpora and grammars, and words that you add directly.
    #
    #   **See also:**
    #   * [Add a corpus to the custom language
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-languageCreate#addCorpus)
    #   * [Working with corpora for previous-generation
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-corporaWords#workingCorpora)
    #   * [Working with corpora for next-generation
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-corporaWords-ng#workingCorpora-ng)
    #
    #   * [Validating a words resource for previous-generation
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-corporaWords#validateModel)
    #
    #   * [Validating a words resource for next-generation
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-corporaWords-ng#validateModel-ng).
    # @param customization_id [String] The customization ID (GUID) of the custom language model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @param corpus_name [String] The name of the new corpus for the custom language model. Use a localized name
    #   that matches the language of the custom model and reflects the contents of the
    #   corpus.
    #   * Include a maximum of 128 characters in the name.
    #   * Do not use characters that need to be URL-encoded. For example, do not use
    #   spaces, slashes, backslashes, colons, ampersands, double quotes, plus signs,
    #   equals signs, questions marks, and so on in the name. (The service does not
    #   prevent the use of these characters. But because they must be URL-encoded wherever
    #   used, their use is strongly discouraged.)
    #   * Do not use the name of an existing corpus or grammar that is already defined for
    #   the custom model.
    #   * Do not use the name `user`, which is reserved by the service to denote custom
    #   words that are added or modified by the user.
    #   * Do not use the name `base_lm` or `default_lm`. Both names are reserved for
    #   future use by the service.
    # @param corpus_file [File] A plain text file that contains the training data for the corpus. Encode the file
    #   in UTF-8 if it contains non-ASCII characters; the service assumes UTF-8 encoding
    #   if it encounters non-ASCII characters.
    #
    #   Make sure that you know the character encoding of the file. You must use that same
    #   encoding when working with the words in the custom language model. For more
    #   information, see [Character encoding for custom
    #   words](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageWords#charEncoding).
    #
    #
    #   With the `curl` command, use the `--data-binary` option to upload the file for the
    #   request.
    # @param allow_overwrite [Boolean] If `true`, the specified corpus overwrites an existing corpus with the same name.
    #   If `false`, the request fails if a corpus with the same name already exists. The
    #   parameter has no effect if a corpus with the same name does not already exist.
    # @return [nil]
    def add_corpus(customization_id:, corpus_name:, corpus_file:, allow_overwrite: nil)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      raise ArgumentError.new("corpus_name must be provided") if corpus_name.nil?

      raise ArgumentError.new("corpus_file must be provided") if corpus_file.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "add_corpus")
      headers.merge!(sdk_headers)

      params = {
        "allow_overwrite" => allow_overwrite
      }

      form_data = {}

      unless corpus_file.instance_of?(StringIO) || corpus_file.instance_of?(File)
        corpus_file = corpus_file.respond_to?(:to_json) ? StringIO.new(corpus_file.to_json) : StringIO.new(corpus_file)
      end
      form_data[:corpus_file] = HTTP::FormData::File.new(corpus_file, content_type: "text/plain", filename: corpus_file.respond_to?(:path) ? corpus_file.path : nil)

      method_url = "/v1/customizations/%s/corpora/%s" % [ERB::Util.url_encode(customization_id), ERB::Util.url_encode(corpus_name)]

      request(
        method: "POST",
        url: method_url,
        headers: headers,
        params: params,
        form: form_data,
        accept_json: true
      )
      nil
    end

    ##
    # @!method get_corpus(customization_id:, corpus_name:)
    # Get a corpus.
    # Gets information about a corpus from a custom language model. The information
    #   includes the name, status, and total number of words for the corpus. _For custom
    #   models that are based on previous-generation models_, it also includes the number
    #   of out-of-vocabulary (OOV) words from the corpus. You must use credentials for the
    #   instance of the service that owns a model to list its corpora.
    #
    #   **See also:** [Listing corpora for a custom language
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageCorpora#listCorpora).
    # @param customization_id [String] The customization ID (GUID) of the custom language model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @param corpus_name [String] The name of the corpus for the custom language model.
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def get_corpus(customization_id:, corpus_name:)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      raise ArgumentError.new("corpus_name must be provided") if corpus_name.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "get_corpus")
      headers.merge!(sdk_headers)

      method_url = "/v1/customizations/%s/corpora/%s" % [ERB::Util.url_encode(customization_id), ERB::Util.url_encode(corpus_name)]

      response = request(
        method: "GET",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      response
    end

    ##
    # @!method delete_corpus(customization_id:, corpus_name:)
    # Delete a corpus.
    # Deletes an existing corpus from a custom language model. Removing a corpus does
    #   not affect the custom model until you train the model with the [Train a custom
    #   language model](#trainlanguagemodel) method. You must use credentials for the
    #   instance of the service that owns a model to delete its corpora.
    #
    #   _For custom models that are based on previous-generation models_, the service
    #   removes any out-of-vocabulary (OOV) words that are associated with the corpus from
    #   the custom model's words resource unless they were also added by another corpus or
    #   grammar, or they were modified in some way with the [Add custom words](#addwords)
    #   or [Add a custom word](#addword) method.
    #
    #
    #
    #   **See also:** [Deleting a corpus from a custom language
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageCorpora#deleteCorpus).
    # @param customization_id [String] The customization ID (GUID) of the custom language model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @param corpus_name [String] The name of the corpus for the custom language model.
    # @return [nil]
    def delete_corpus(customization_id:, corpus_name:)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      raise ArgumentError.new("corpus_name must be provided") if corpus_name.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "delete_corpus")
      headers.merge!(sdk_headers)

      method_url = "/v1/customizations/%s/corpora/%s" % [ERB::Util.url_encode(customization_id), ERB::Util.url_encode(corpus_name)]

      request(
        method: "DELETE",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      nil
    end
    #########################
    # Custom words
    #########################

    ##
    # @!method list_words(customization_id:, word_type: nil, sort: nil)
    # List custom words.
    # Lists information about custom words from a custom language model. You can list
    #   all words from the custom model's words resource, only custom words that were
    #   added or modified by the user, or, _for a custom model that is based on a
    #   previous-generation model_, only out-of-vocabulary (OOV) words that were extracted
    #   from corpora or are recognized by grammars. You can also indicate the order in
    #   which the service is to return words; by default, the service lists words in
    #   ascending alphabetical order. You must use credentials for the instance of the
    #   service that owns a model to list information about its words.
    #
    #   **See also:** [Listing words from a custom language
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageWords#listWords).
    # @param customization_id [String] The customization ID (GUID) of the custom language model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @param word_type [String] The type of words to be listed from the custom language model's words resource:
    #   * `all` (the default) shows all words.
    #   * `user` shows only custom words that were added or modified by the user directly.
    #   * `corpora` shows only OOV that were extracted from corpora.
    #   * `grammars` shows only OOV words that are recognized by grammars.
    #
    #   _For a custom model that is based on a next-generation model_, only `all` and
    #   `user` apply. Both options return the same results. Words from other sources are
    #   not added to custom models that are based on next-generation models.
    # @param sort [String] Indicates the order in which the words are to be listed, `alphabetical` or by
    #   `count`. You can prepend an optional `+` or `-` to an argument to indicate whether
    #   the results are to be sorted in ascending or descending order. By default, words
    #   are sorted in ascending alphabetical order. For alphabetical ordering, the
    #   lexicographical precedence is numeric values, uppercase letters, and lowercase
    #   letters. For count ordering, values with the same count are ordered
    #   alphabetically. With the `curl` command, URL-encode the `+` symbol as `%2B`.
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def list_words(customization_id:, word_type: nil, sort: nil)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "list_words")
      headers.merge!(sdk_headers)

      params = {
        "word_type" => word_type,
        "sort" => sort
      }

      method_url = "/v1/customizations/%s/words" % [ERB::Util.url_encode(customization_id)]

      response = request(
        method: "GET",
        url: method_url,
        headers: headers,
        params: params,
        accept_json: true
      )
      response
    end

    ##
    # @!method add_words(customization_id:, words:)
    # Add custom words.
    # Adds one or more custom words to a custom language model. You can use this method
    #   to add words or to modify existing words in a custom model's words resource. _For
    #   custom models that are based on previous-generation models_, the service populates
    #   the words resource for a custom model with out-of-vocabulary (OOV) words from each
    #   corpus or grammar that is added to the model. You can use this method to modify
    #   OOV words in the model's words resource.
    #
    #   _For a custom model that is based on a previous-generation model_, the words
    #   resource for a model can contain a maximum of 90 thousand custom (OOV) words. This
    #   includes words that the service extracts from corpora and grammars and words that
    #   you add directly.
    #
    #   You must use credentials for the instance of the service that owns a model to add
    #   or modify custom words for the model. Adding or modifying custom words does not
    #   affect the custom model until you train the model for the new data by using the
    #   [Train a custom language model](#trainlanguagemodel) method.
    #
    #   You add custom words by providing a `CustomWords` object, which is an array of
    #   `CustomWord` objects, one per word. Use the object's `word` parameter to identify
    #   the word that is to be added. You can also provide one or both of the optional
    #   `display_as` or `sounds_like` fields for each word.
    #   * The `display_as` field provides a different way of spelling the word in a
    #   transcript. Use the parameter when you want the word to appear different from its
    #   usual representation or from its spelling in training data. For example, you might
    #   indicate that the word `IBM` is to be displayed as `IBM&trade;`.
    #   * The `sounds_like` field, _which can be used only with a custom model that is
    #   based on a previous-generation model_, provides an array of one or more
    #   pronunciations for the word. Use the parameter to specify how the word can be
    #   pronounced by users. Use the parameter for words that are difficult to pronounce,
    #   foreign words, acronyms, and so on. For example, you might specify that the word
    #   `IEEE` can sound like `i triple e`. You can specify a maximum of five sounds-like
    #   pronunciations for a word. If you omit the `sounds_like` field, the service
    #   attempts to set the field to its pronunciation of the word. It cannot generate a
    #   pronunciation for all words, so you must review the word's definition to ensure
    #   that it is complete and valid.
    #
    #   If you add a custom word that already exists in the words resource for the custom
    #   model, the new definition overwrites the existing data for the word. If the
    #   service encounters an error with the input data, it returns a failure code and
    #   does not add any of the words to the words resource.
    #
    #   The call returns an HTTP 201 response code if the input data is valid. It then
    #   asynchronously processes the words to add them to the model's words resource. The
    #   time that it takes for the analysis to complete depends on the number of new words
    #   that you add but is generally faster than adding a corpus or grammar.
    #
    #   You can monitor the status of the request by using the [Get a custom language
    #   model](#getlanguagemodel) method to poll the model's status. Use a loop to check
    #   the status every 10 seconds. The method returns a `Customization` object that
    #   includes a `status` field. A status of `ready` means that the words have been
    #   added to the custom model. The service cannot accept requests to add new data or
    #   to train the model until the existing request completes.
    #
    #   You can use the [List custom words](#listwords) or [Get a custom word](#getword)
    #   method to review the words that you add. Words with an invalid `sounds_like` field
    #   include an `error` field that describes the problem. You can use other
    #   words-related methods to correct errors, eliminate typos, and modify how words are
    #   pronounced as needed.
    #
    #   **See also:**
    #   * [Add words to the custom language
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-languageCreate#addWords)
    #   * [Working with custom words for previous-generation
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-corporaWords#workingWords)
    #   * [Working with custom words for next-generation
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-corporaWords-ng#workingWords-ng)
    #   * [Validating a words resource for previous-generation
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-corporaWords#validateModel)
    #   * [Validating a words resource for next-generation
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-corporaWords-ng#validateModel-ng).
    # @param customization_id [String] The customization ID (GUID) of the custom language model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @param words [Array[CustomWord]] An array of `CustomWord` objects that provides information about each custom word
    #   that is to be added to or updated in the custom language model.
    # @return [nil]
    def add_words(customization_id:, words:)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      raise ArgumentError.new("words must be provided") if words.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "add_words")
      headers.merge!(sdk_headers)

      data = {
        "words" => words
      }

      method_url = "/v1/customizations/%s/words" % [ERB::Util.url_encode(customization_id)]

      request(
        method: "POST",
        url: method_url,
        headers: headers,
        json: data,
        accept_json: true
      )
      nil
    end

    ##
    # @!method add_word(customization_id:, word_name:, word: nil, sounds_like: nil, display_as: nil)
    # Add a custom word.
    # Adds a custom word to a custom language model. You can use this method to add a
    #   word or to modify an existing word in the words resource. _For custom models that
    #   are based on previous-generation models_, the service populates the words resource
    #   for a custom model with out-of-vocabulary (OOV) words from each corpus or grammar
    #   that is added to the model. You can use this method to modify OOV words in the
    #   model's words resource.
    #
    #   _For a custom model that is based on a previous-generation models_, the words
    #   resource for a model can contain a maximum of 90 thousand custom (OOV) words. This
    #   includes words that the service extracts from corpora and grammars and words that
    #   you add directly.
    #
    #   You must use credentials for the instance of the service that owns a model to add
    #   or modify a custom word for the model. Adding or modifying a custom word does not
    #   affect the custom model until you train the model for the new data by using the
    #   [Train a custom language model](#trainlanguagemodel) method.
    #
    #   Use the `word_name` parameter to specify the custom word that is to be added or
    #   modified. Use the `CustomWord` object to provide one or both of the optional
    #   `display_as` or `sounds_like` fields for the word.
    #   * The `display_as` field provides a different way of spelling the word in a
    #   transcript. Use the parameter when you want the word to appear different from its
    #   usual representation or from its spelling in training data. For example, you might
    #   indicate that the word `IBM` is to be displayed as `IBM&trade;`.
    #   * The `sounds_like` field, _which can be used only with a custom model that is
    #   based on a previous-generation model_, provides an array of one or more
    #   pronunciations for the word. Use the parameter to specify how the word can be
    #   pronounced by users. Use the parameter for words that are difficult to pronounce,
    #   foreign words, acronyms, and so on. For example, you might specify that the word
    #   `IEEE` can sound like `i triple e`. You can specify a maximum of five sounds-like
    #   pronunciations for a word. If you omit the `sounds_like` field, the service
    #   attempts to set the field to its pronunciation of the word. It cannot generate a
    #   pronunciation for all words, so you must review the word's definition to ensure
    #   that it is complete and valid.
    #
    #   If you add a custom word that already exists in the words resource for the custom
    #   model, the new definition overwrites the existing data for the word. If the
    #   service encounters an error, it does not add the word to the words resource. Use
    #   the [Get a custom word](#getword) method to review the word that you add.
    #
    #   **See also:**
    #   * [Add words to the custom language
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-languageCreate#addWords)
    #   * [Working with custom words for previous-generation
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-corporaWords#workingWords)
    #   * [Working with custom words for next-generation
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-corporaWords-ng#workingWords-ng)
    #   * [Validating a words resource for previous-generation
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-corporaWords#validateModel)
    #   * [Validating a words resource for next-generation
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-corporaWords-ng#validateModel-ng).
    # @param customization_id [String] The customization ID (GUID) of the custom language model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @param word_name [String] The custom word that is to be added to or updated in the custom language model. Do
    #   not include spaces in the word. Use a `-` (dash) or `_` (underscore) to connect
    #   the tokens of compound words. URL-encode the word if it includes non-ASCII
    #   characters. For more information, see [Character
    #   encoding](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-corporaWords#charEncoding).
    # @param word [String] For the [Add custom words](#addwords) method, you must specify the custom word
    #   that is to be added to or updated in the custom model. Do not include spaces in
    #   the word. Use a `-` (dash) or `_` (underscore) to connect the tokens of compound
    #   words.
    #
    #   Omit this parameter for the [Add a custom word](#addword) method.
    # @param sounds_like [Array[String]] _For a custom model that is based on a previous-generation model_, an array of
    #   sounds-like pronunciations for the custom word. Specify how words that are
    #   difficult to pronounce, foreign words, acronyms, and so on can be pronounced by
    #   users.
    #   * For a word that is not in the service's base vocabulary, omit the parameter to
    #   have the service automatically generate a sounds-like pronunciation for the word.
    #   * For a word that is in the service's base vocabulary, use the parameter to
    #   specify additional pronunciations for the word. You cannot override the default
    #   pronunciation of a word; pronunciations you add augment the pronunciation from the
    #   base vocabulary.
    #
    #   A word can have at most five sounds-like pronunciations. A pronunciation can
    #   include at most 40 characters not including spaces.
    #
    #   _For a custom model that is based on a next-generation model_, omit this field.
    #   Custom models based on next-generation models do not support the `sounds_like`
    #   field. The service ignores the field.
    # @param display_as [String] An alternative spelling for the custom word when it appears in a transcript. Use
    #   the parameter when you want the word to have a spelling that is different from its
    #   usual representation or from its spelling in corpora training data.
    # @return [nil]
    def add_word(customization_id:, word_name:, word: nil, sounds_like: nil, display_as: nil)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      raise ArgumentError.new("word_name must be provided") if word_name.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "add_word")
      headers.merge!(sdk_headers)

      data = {
        "word" => word,
        "sounds_like" => sounds_like,
        "display_as" => display_as
      }

      method_url = "/v1/customizations/%s/words/%s" % [ERB::Util.url_encode(customization_id), ERB::Util.url_encode(word_name)]

      request(
        method: "PUT",
        url: method_url,
        headers: headers,
        json: data,
        accept_json: true
      )
      nil
    end

    ##
    # @!method get_word(customization_id:, word_name:)
    # Get a custom word.
    # Gets information about a custom word from a custom language model. You must use
    #   credentials for the instance of the service that owns a model to list information
    #   about its words.
    #
    #   **See also:** [Listing words from a custom language
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageWords#listWords).
    # @param customization_id [String] The customization ID (GUID) of the custom language model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @param word_name [String] The custom word that is to be read from the custom language model. URL-encode the
    #   word if it includes non-ASCII characters. For more information, see [Character
    #   encoding](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-corporaWords#charEncoding).
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def get_word(customization_id:, word_name:)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      raise ArgumentError.new("word_name must be provided") if word_name.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "get_word")
      headers.merge!(sdk_headers)

      method_url = "/v1/customizations/%s/words/%s" % [ERB::Util.url_encode(customization_id), ERB::Util.url_encode(word_name)]

      response = request(
        method: "GET",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      response
    end

    ##
    # @!method delete_word(customization_id:, word_name:)
    # Delete a custom word.
    # Deletes a custom word from a custom language model. You can remove any word that
    #   you added to the custom model's words resource via any means. However, if the word
    #   also exists in the service's base vocabulary, the service removes the word only
    #   from the words resource; the word remains in the base vocabulary. Removing a
    #   custom word does not affect the custom model until you train the model with the
    #   [Train a custom language model](#trainlanguagemodel) method. You must use
    #   credentials for the instance of the service that owns a model to delete its words.
    #
    #
    #   **See also:** [Deleting a word from a custom language
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageWords#deleteWord).
    # @param customization_id [String] The customization ID (GUID) of the custom language model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @param word_name [String] The custom word that is to be deleted from the custom language model. URL-encode
    #   the word if it includes non-ASCII characters. For more information, see [Character
    #   encoding](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-corporaWords#charEncoding).
    # @return [nil]
    def delete_word(customization_id:, word_name:)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      raise ArgumentError.new("word_name must be provided") if word_name.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "delete_word")
      headers.merge!(sdk_headers)

      method_url = "/v1/customizations/%s/words/%s" % [ERB::Util.url_encode(customization_id), ERB::Util.url_encode(word_name)]

      request(
        method: "DELETE",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      nil
    end
    #########################
    # Custom grammars
    #########################

    ##
    # @!method list_grammars(customization_id:)
    # List grammars.
    # Lists information about all grammars from a custom language model. For each
    #   grammar, the information includes the name, status, and (for grammars that are
    #   based on previous-generation models) the total number of out-of-vocabulary (OOV)
    #   words. You must use credentials for the instance of the service that owns a model
    #   to list its grammars.
    #
    #   **See also:**
    #   * [Listing grammars from a custom language
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageGrammars#listGrammars)
    #   * [Language support for
    #   customization](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-support).
    # @param customization_id [String] The customization ID (GUID) of the custom language model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def list_grammars(customization_id:)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "list_grammars")
      headers.merge!(sdk_headers)

      method_url = "/v1/customizations/%s/grammars" % [ERB::Util.url_encode(customization_id)]

      response = request(
        method: "GET",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      response
    end

    ##
    # @!method add_grammar(customization_id:, grammar_name:, grammar_file:, content_type:, allow_overwrite: nil)
    # Add a grammar.
    # Adds a single grammar file to a custom language model. Submit a plain text file in
    #   UTF-8 format that defines the grammar. Use multiple requests to submit multiple
    #   grammar files. You must use credentials for the instance of the service that owns
    #   a model to add a grammar to it. Adding a grammar does not affect the custom
    #   language model until you train the model for the new data by using the [Train a
    #   custom language model](#trainlanguagemodel) method.
    #
    #   The call returns an HTTP 201 response code if the grammar is valid. The service
    #   then asynchronously processes the contents of the grammar and automatically
    #   extracts new words that it finds. This operation can take a few seconds or minutes
    #   to complete depending on the size and complexity of the grammar, as well as the
    #   current load on the service. You cannot submit requests to add additional
    #   resources to the custom model or to train the model until the service's analysis
    #   of the grammar for the current request completes. Use the [Get a
    #   grammar](#getgrammar) method to check the status of the analysis.
    #
    #   _For grammars that are based on previous-generation models,_ the service populates
    #   the model's words resource with any word that is recognized by the grammar that is
    #   not found in the model's base vocabulary. These are referred to as
    #   out-of-vocabulary (OOV) words. You can use the [List custom words](#listwords)
    #   method to examine the words resource and use other words-related methods to
    #   eliminate typos and modify how words are pronounced as needed. _For grammars that
    #   are based on next-generation models,_ the service extracts no OOV words from the
    #   grammars.
    #
    #   To add a grammar that has the same name as an existing grammar, set the
    #   `allow_overwrite` parameter to `true`; otherwise, the request fails. Overwriting
    #   an existing grammar causes the service to process the grammar file and extract OOV
    #   words anew. Before doing so, it removes any OOV words associated with the existing
    #   grammar from the model's words resource unless they were also added by another
    #   resource or they have been modified in some way with the [Add custom
    #   words](#addwords) or [Add a custom word](#addword) method.
    #
    #   _For grammars that are based on previous-generation models,_ the service limits
    #   the overall amount of data that you can add to a custom model to a maximum of 10
    #   million total words from all sources combined. Also, you can add no more than 90
    #   thousand OOV words to a model. This includes words that the service extracts from
    #   corpora and grammars and words that you add directly.
    #
    #   **See also:**
    #   * [Understanding
    #   grammars](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-grammarUnderstand#grammarUnderstand)
    #   * [Add a grammar to the custom language
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-grammarAdd#addGrammar)
    #   * [Language support for
    #   customization](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-support).
    # @param customization_id [String] The customization ID (GUID) of the custom language model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @param grammar_name [String] The name of the new grammar for the custom language model. Use a localized name
    #   that matches the language of the custom model and reflects the contents of the
    #   grammar.
    #   * Include a maximum of 128 characters in the name.
    #   * Do not use characters that need to be URL-encoded. For example, do not use
    #   spaces, slashes, backslashes, colons, ampersands, double quotes, plus signs,
    #   equals signs, questions marks, and so on in the name. (The service does not
    #   prevent the use of these characters. But because they must be URL-encoded wherever
    #   used, their use is strongly discouraged.)
    #   * Do not use the name of an existing grammar or corpus that is already defined for
    #   the custom model.
    #   * Do not use the name `user`, which is reserved by the service to denote custom
    #   words that are added or modified by the user.
    #   * Do not use the name `base_lm` or `default_lm`. Both names are reserved for
    #   future use by the service.
    # @param grammar_file [File] A plain text file that contains the grammar in the format specified by the
    #   `Content-Type` header. Encode the file in UTF-8 (ASCII is a subset of UTF-8).
    #   Using any other encoding can lead to issues when compiling the grammar or to
    #   unexpected results in decoding. The service ignores an encoding that is specified
    #   in the header of the grammar.
    #
    #   With the `curl` command, use the `--data-binary` option to upload the file for the
    #   request.
    # @param content_type [String] The format (MIME type) of the grammar file:
    #   * `application/srgs` for Augmented Backus-Naur Form (ABNF), which uses a
    #   plain-text representation that is similar to traditional BNF grammars.
    #   * `application/srgs+xml` for XML Form, which uses XML elements to represent the
    #   grammar.
    # @param allow_overwrite [Boolean] If `true`, the specified grammar overwrites an existing grammar with the same
    #   name. If `false`, the request fails if a grammar with the same name already
    #   exists. The parameter has no effect if a grammar with the same name does not
    #   already exist.
    # @return [nil]
    def add_grammar(customization_id:, grammar_name:, grammar_file:, content_type:, allow_overwrite: nil)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      raise ArgumentError.new("grammar_name must be provided") if grammar_name.nil?

      raise ArgumentError.new("grammar_file must be provided") if grammar_file.nil?

      raise ArgumentError.new("content_type must be provided") if content_type.nil?

      headers = {
        "Content-Type" => content_type
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "add_grammar")
      headers.merge!(sdk_headers)

      params = {
        "allow_overwrite" => allow_overwrite
      }

      data = grammar_file

      method_url = "/v1/customizations/%s/grammars/%s" % [ERB::Util.url_encode(customization_id), ERB::Util.url_encode(grammar_name)]

      request(
        method: "POST",
        url: method_url,
        headers: headers,
        params: params,
        data: data,
        accept_json: true
      )
      nil
    end

    ##
    # @!method get_grammar(customization_id:, grammar_name:)
    # Get a grammar.
    # Gets information about a grammar from a custom language model. For each grammar,
    #   the information includes the name, status, and (for grammars that are based on
    #   previous-generation models) the total number of out-of-vocabulary (OOV) words. You
    #   must use credentials for the instance of the service that owns a model to list its
    #   grammars.
    #
    #   **See also:**
    #   * [Listing grammars from a custom language
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageGrammars#listGrammars)
    #   * [Language support for
    #   customization](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-support).
    # @param customization_id [String] The customization ID (GUID) of the custom language model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @param grammar_name [String] The name of the grammar for the custom language model.
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def get_grammar(customization_id:, grammar_name:)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      raise ArgumentError.new("grammar_name must be provided") if grammar_name.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "get_grammar")
      headers.merge!(sdk_headers)

      method_url = "/v1/customizations/%s/grammars/%s" % [ERB::Util.url_encode(customization_id), ERB::Util.url_encode(grammar_name)]

      response = request(
        method: "GET",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      response
    end

    ##
    # @!method delete_grammar(customization_id:, grammar_name:)
    # Delete a grammar.
    # Deletes an existing grammar from a custom language model. _For grammars that are
    #   based on previous-generation models,_ the service removes any out-of-vocabulary
    #   (OOV) words associated with the grammar from the custom model's words resource
    #   unless they were also added by another resource or they were modified in some way
    #   with the [Add custom words](#addwords) or [Add a custom word](#addword) method.
    #   Removing a grammar does not affect the custom model until you train the model with
    #   the [Train a custom language model](#trainlanguagemodel) method. You must use
    #   credentials for the instance of the service that owns a model to delete its
    #   grammar.
    #
    #   **See also:**
    #   * [Deleting a grammar from a custom language
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageGrammars#deleteGrammar)
    #   * [Language support for
    #   customization](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-support).
    # @param customization_id [String] The customization ID (GUID) of the custom language model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @param grammar_name [String] The name of the grammar for the custom language model.
    # @return [nil]
    def delete_grammar(customization_id:, grammar_name:)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      raise ArgumentError.new("grammar_name must be provided") if grammar_name.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "delete_grammar")
      headers.merge!(sdk_headers)

      method_url = "/v1/customizations/%s/grammars/%s" % [ERB::Util.url_encode(customization_id), ERB::Util.url_encode(grammar_name)]

      request(
        method: "DELETE",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      nil
    end
    #########################
    # Custom acoustic models
    #########################

    ##
    # @!method create_acoustic_model(name:, base_model_name:, description: nil)
    # Create a custom acoustic model.
    # Creates a new custom acoustic model for a specified base model. The custom
    #   acoustic model can be used only with the base model for which it is created. The
    #   model is owned by the instance of the service whose credentials are used to create
    #   it.
    #
    #   You can create a maximum of 1024 custom acoustic models per owning credentials.
    #   The service returns an error if you attempt to create more than 1024 models. You
    #   do not lose any models, but you cannot create any more until your model count is
    #   below the limit.
    #
    #   **Note:** Acoustic model customization is supported only for use with
    #   previous-generation models. It is not supported for next-generation models.
    #
    #   **Important:** Effective 15 March 2022, previous-generation models for all
    #   languages other than Arabic and Japanese are deprecated. The deprecated models
    #   remain available until 15 September 2022, when they will be removed from the
    #   service and the documentation. You must migrate to the equivalent next-generation
    #   model by the end of service date. For more information, see [Migrating to
    #   next-generation
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-migrate).
    #
    #
    #   **See also:** [Create a custom acoustic
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-acoustic#createModel-acoustic).
    # @param name [String] A user-defined name for the new custom acoustic model. Use a name that is unique
    #   among all custom acoustic models that you own. Use a localized name that matches
    #   the language of the custom model. Use a name that describes the acoustic
    #   environment of the custom model, such as `Mobile custom model` or `Noisy car
    #   custom model`.
    # @param base_model_name [String] The name of the base language model that is to be customized by the new custom
    #   acoustic model. The new custom model can be used only with the base model that it
    #   customizes. (**Note:** The model `ar-AR_BroadbandModel` is deprecated; use
    #   `ar-MS_BroadbandModel` instead.)
    #
    #   To determine whether a base model supports acoustic model customization, refer to
    #   [Language support for
    #   customization](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-support).
    # @param description [String] A description of the new custom acoustic model. Use a localized description that
    #   matches the language of the custom model.
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def create_acoustic_model(name:, base_model_name:, description: nil)
      raise ArgumentError.new("name must be provided") if name.nil?

      raise ArgumentError.new("base_model_name must be provided") if base_model_name.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "create_acoustic_model")
      headers.merge!(sdk_headers)

      data = {
        "name" => name,
        "base_model_name" => base_model_name,
        "description" => description
      }

      method_url = "/v1/acoustic_customizations"

      response = request(
        method: "POST",
        url: method_url,
        headers: headers,
        json: data,
        accept_json: true
      )
      response
    end

    ##
    # @!method list_acoustic_models(language: nil)
    # List custom acoustic models.
    # Lists information about all custom acoustic models that are owned by an instance
    #   of the service. Use the `language` parameter to see all custom acoustic models for
    #   the specified language. Omit the parameter to see all custom acoustic models for
    #   all languages. You must use credentials for the instance of the service that owns
    #   a model to list information about it.
    #
    #   **Note:** Acoustic model customization is supported only for use with
    #   previous-generation models. It is not supported for next-generation models.
    #
    #   **See also:** [Listing custom acoustic
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageAcousticModels#listModels-acoustic).
    # @param language [String] The identifier of the language for which custom language or custom acoustic models
    #   are to be returned. Specify the five-character language identifier; for example,
    #   specify `en-US` to see all custom language or custom acoustic models that are
    #   based on US English models. Omit the parameter to see all custom language or
    #   custom acoustic models that are owned by the requesting credentials. (**Note:**
    #   The identifier `ar-AR` is deprecated; use `ar-MS` instead.)
    #
    #   To determine the languages for which customization is available, see [Language
    #   support for
    #   customization](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-support).
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def list_acoustic_models(language: nil)
      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "list_acoustic_models")
      headers.merge!(sdk_headers)

      params = {
        "language" => language
      }

      method_url = "/v1/acoustic_customizations"

      response = request(
        method: "GET",
        url: method_url,
        headers: headers,
        params: params,
        accept_json: true
      )
      response
    end

    ##
    # @!method get_acoustic_model(customization_id:)
    # Get a custom acoustic model.
    # Gets information about a specified custom acoustic model. You must use credentials
    #   for the instance of the service that owns a model to list information about it.
    #
    #   **Note:** Acoustic model customization is supported only for use with
    #   previous-generation models. It is not supported for next-generation models.
    #
    #   **See also:** [Listing custom acoustic
    #   models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageAcousticModels#listModels-acoustic).
    # @param customization_id [String] The customization ID (GUID) of the custom acoustic model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def get_acoustic_model(customization_id:)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "get_acoustic_model")
      headers.merge!(sdk_headers)

      method_url = "/v1/acoustic_customizations/%s" % [ERB::Util.url_encode(customization_id)]

      response = request(
        method: "GET",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      response
    end

    ##
    # @!method delete_acoustic_model(customization_id:)
    # Delete a custom acoustic model.
    # Deletes an existing custom acoustic model. The custom model cannot be deleted if
    #   another request, such as adding an audio resource to the model, is currently being
    #   processed. You must use credentials for the instance of the service that owns a
    #   model to delete it.
    #
    #   **Note:** Acoustic model customization is supported only for use with
    #   previous-generation models. It is not supported for next-generation models.
    #
    #   **See also:** [Deleting a custom acoustic
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageAcousticModels#deleteModel-acoustic).
    # @param customization_id [String] The customization ID (GUID) of the custom acoustic model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @return [nil]
    def delete_acoustic_model(customization_id:)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "delete_acoustic_model")
      headers.merge!(sdk_headers)

      method_url = "/v1/acoustic_customizations/%s" % [ERB::Util.url_encode(customization_id)]

      request(
        method: "DELETE",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      nil
    end

    ##
    # @!method train_acoustic_model(customization_id:, custom_language_model_id: nil)
    # Train a custom acoustic model.
    # Initiates the training of a custom acoustic model with new or changed audio
    #   resources. After adding or deleting audio resources for a custom acoustic model,
    #   use this method to begin the actual training of the model on the latest audio
    #   data. The custom acoustic model does not reflect its changed data until you train
    #   it. You must use credentials for the instance of the service that owns a model to
    #   train it.
    #
    #   The training method is asynchronous. Training time depends on the cumulative
    #   amount of audio data that the custom acoustic model contains and the current load
    #   on the service. When you train or retrain a model, the service uses all of the
    #   model's audio data in the training. Training a custom acoustic model takes
    #   approximately as long as the length of its cumulative audio data. For example, it
    #   takes approximately 2 hours to train a model that contains a total of 2 hours of
    #   audio. The method returns an HTTP 200 response code to indicate that the training
    #   process has begun.
    #
    #   You can monitor the status of the training by using the [Get a custom acoustic
    #   model](#getacousticmodel) method to poll the model's status. Use a loop to check
    #   the status once a minute. The method returns an `AcousticModel` object that
    #   includes `status` and `progress` fields. A status of `available` indicates that
    #   the custom model is trained and ready to use. The service cannot train a model
    #   while it is handling another request for the model. The service cannot accept
    #   subsequent training requests, or requests to add new audio resources, until the
    #   existing training request completes.
    #
    #   You can use the optional `custom_language_model_id` parameter to specify the GUID
    #   of a separately created custom language model that is to be used during training.
    #   Train with a custom language model if you have verbatim transcriptions of the
    #   audio files that you have added to the custom model or you have either corpora
    #   (text files) or a list of words that are relevant to the contents of the audio
    #   files. For training to succeed, both of the custom models must be based on the
    #   same version of the same base model, and the custom language model must be fully
    #   trained and available.
    #
    #   **Note:** Acoustic model customization is supported only for use with
    #   previous-generation models. It is not supported for next-generation models.
    #
    #   **See also:**
    #   * [Train the custom acoustic
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-acoustic#trainModel-acoustic)
    #   * [Using custom acoustic and custom language models
    #   together](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-useBoth#useBoth)
    #
    #
    #   ### Training failures
    #
    #    Training can fail to start for the following reasons:
    #   * The service is currently handling another request for the custom model, such as
    #   another training request or a request to add audio resources to the model.
    #   * The custom model contains less than 10 minutes or more than 200 hours of audio
    #   data.
    #   * You passed a custom language model with the `custom_language_model_id` query
    #   parameter that is not in the available state. A custom language model must be
    #   fully trained and available to be used to train a custom acoustic model.
    #   * You passed an incompatible custom language model with the
    #   `custom_language_model_id` query parameter. Both custom models must be based on
    #   the same version of the same base model.
    #   * The custom model contains one or more invalid audio resources. You can correct
    #   the invalid audio resources or set the `strict` parameter to `false` to exclude
    #   the invalid resources from the training. The model must contain at least one valid
    #   resource for training to succeed.
    # @param customization_id [String] The customization ID (GUID) of the custom acoustic model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @param custom_language_model_id [String] The customization ID (GUID) of a custom language model that is to be used during
    #   training of the custom acoustic model. Specify a custom language model that has
    #   been trained with verbatim transcriptions of the audio resources or that contains
    #   words that are relevant to the contents of the audio resources. The custom
    #   language model must be based on the same version of the same base model as the
    #   custom acoustic model, and the custom language model must be fully trained and
    #   available. The credentials specified with the request must own both custom models.
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def train_acoustic_model(customization_id:, custom_language_model_id: nil)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "train_acoustic_model")
      headers.merge!(sdk_headers)

      params = {
        "custom_language_model_id" => custom_language_model_id
      }

      method_url = "/v1/acoustic_customizations/%s/train" % [ERB::Util.url_encode(customization_id)]

      response = request(
        method: "POST",
        url: method_url,
        headers: headers,
        params: params,
        accept_json: true
      )
      response
    end

    ##
    # @!method reset_acoustic_model(customization_id:)
    # Reset a custom acoustic model.
    # Resets a custom acoustic model by removing all audio resources from the model.
    #   Resetting a custom acoustic model initializes the model to its state when it was
    #   first created. Metadata such as the name and language of the model are preserved,
    #   but the model's audio resources are removed and must be re-created. The service
    #   cannot reset a model while it is handling another request for the model. The
    #   service cannot accept subsequent requests for the model until the existing reset
    #   request completes. You must use credentials for the instance of the service that
    #   owns a model to reset it.
    #
    #   **Note:** Acoustic model customization is supported only for use with
    #   previous-generation models. It is not supported for next-generation models.
    #
    #   **See also:** [Resetting a custom acoustic
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageAcousticModels#resetModel-acoustic).
    # @param customization_id [String] The customization ID (GUID) of the custom acoustic model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @return [nil]
    def reset_acoustic_model(customization_id:)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "reset_acoustic_model")
      headers.merge!(sdk_headers)

      method_url = "/v1/acoustic_customizations/%s/reset" % [ERB::Util.url_encode(customization_id)]

      request(
        method: "POST",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      nil
    end

    ##
    # @!method upgrade_acoustic_model(customization_id:, custom_language_model_id: nil, force: nil)
    # Upgrade a custom acoustic model.
    # Initiates the upgrade of a custom acoustic model to the latest version of its base
    #   language model. The upgrade method is asynchronous. It can take on the order of
    #   minutes or hours to complete depending on the amount of data in the custom model
    #   and the current load on the service; typically, upgrade takes approximately twice
    #   the length of the total audio contained in the custom model. A custom model must
    #   be in the `ready` or `available` state to be upgraded. You must use credentials
    #   for the instance of the service that owns a model to upgrade it.
    #
    #   The method returns an HTTP 200 response code to indicate that the upgrade process
    #   has begun successfully. You can monitor the status of the upgrade by using the
    #   [Get a custom acoustic model](#getacousticmodel) method to poll the model's
    #   status. The method returns an `AcousticModel` object that includes `status` and
    #   `progress` fields. Use a loop to check the status once a minute.
    #
    #   While it is being upgraded, the custom model has the status `upgrading`. When the
    #   upgrade is complete, the model resumes the status that it had prior to upgrade.
    #   The service cannot upgrade a model while it is handling another request for the
    #   model. The service cannot accept subsequent requests for the model until the
    #   existing upgrade request completes.
    #
    #   If the custom acoustic model was trained with a separately created custom language
    #   model, you must use the `custom_language_model_id` parameter to specify the GUID
    #   of that custom language model. The custom language model must be upgraded before
    #   the custom acoustic model can be upgraded. Omit the parameter if the custom
    #   acoustic model was not trained with a custom language model.
    #
    #   **Note:** Acoustic model customization is supported only for use with
    #   previous-generation models. It is not supported for next-generation models.
    #
    #   **See also:** [Upgrading a custom acoustic
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-upgrade#custom-upgrade-acoustic).
    # @param customization_id [String] The customization ID (GUID) of the custom acoustic model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @param custom_language_model_id [String] If the custom acoustic model was trained with a custom language model, the
    #   customization ID (GUID) of that custom language model. The custom language model
    #   must be upgraded before the custom acoustic model can be upgraded. The custom
    #   language model must be fully trained and available. The credentials specified with
    #   the request must own both custom models.
    # @param force [Boolean] If `true`, forces the upgrade of a custom acoustic model for which no input data
    #   has been modified since it was last trained. Use this parameter only to force the
    #   upgrade of a custom acoustic model that is trained with a custom language model,
    #   and only if you receive a 400 response code and the message `No input data
    #   modified since last training`. See [Upgrading a custom acoustic
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-upgrade#custom-upgrade-acoustic).
    # @return [nil]
    def upgrade_acoustic_model(customization_id:, custom_language_model_id: nil, force: nil)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "upgrade_acoustic_model")
      headers.merge!(sdk_headers)

      params = {
        "custom_language_model_id" => custom_language_model_id,
        "force" => force
      }

      method_url = "/v1/acoustic_customizations/%s/upgrade_model" % [ERB::Util.url_encode(customization_id)]

      request(
        method: "POST",
        url: method_url,
        headers: headers,
        params: params,
        accept_json: true
      )
      nil
    end
    #########################
    # Custom audio resources
    #########################

    ##
    # @!method list_audio(customization_id:)
    # List audio resources.
    # Lists information about all audio resources from a custom acoustic model. The
    #   information includes the name of the resource and information about its audio
    #   data, such as its duration. It also includes the status of the audio resource,
    #   which is important for checking the service's analysis of the resource in response
    #   to a request to add it to the custom acoustic model. You must use credentials for
    #   the instance of the service that owns a model to list its audio resources.
    #
    #   **Note:** Acoustic model customization is supported only for use with
    #   previous-generation models. It is not supported for next-generation models.
    #
    #   **See also:** [Listing audio resources for a custom acoustic
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageAudio#listAudio).
    # @param customization_id [String] The customization ID (GUID) of the custom acoustic model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def list_audio(customization_id:)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "list_audio")
      headers.merge!(sdk_headers)

      method_url = "/v1/acoustic_customizations/%s/audio" % [ERB::Util.url_encode(customization_id)]

      response = request(
        method: "GET",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      response
    end

    ##
    # @!method add_audio(customization_id:, audio_name:, audio_resource:, content_type: nil, contained_content_type: nil, allow_overwrite: nil)
    # Add an audio resource.
    # Adds an audio resource to a custom acoustic model. Add audio content that reflects
    #   the acoustic characteristics of the audio that you plan to transcribe. You must
    #   use credentials for the instance of the service that owns a model to add an audio
    #   resource to it. Adding audio data does not affect the custom acoustic model until
    #   you train the model for the new data by using the [Train a custom acoustic
    #   model](#trainacousticmodel) method.
    #
    #   You can add individual audio files or an archive file that contains multiple audio
    #   files. Adding multiple audio files via a single archive file is significantly more
    #   efficient than adding each file individually. You can add audio resources in any
    #   format that the service supports for speech recognition.
    #
    #   You can use this method to add any number of audio resources to a custom model by
    #   calling the method once for each audio or archive file. You can add multiple
    #   different audio resources at the same time. You must add a minimum of 10 minutes
    #   and a maximum of 200 hours of audio that includes speech, not just silence, to a
    #   custom acoustic model before you can train it. No audio resource, audio- or
    #   archive-type, can be larger than 100 MB. To add an audio resource that has the
    #   same name as an existing audio resource, set the `allow_overwrite` parameter to
    #   `true`; otherwise, the request fails.
    #
    #   The method is asynchronous. It can take several seconds or minutes to complete
    #   depending on the duration of the audio and, in the case of an archive file, the
    #   total number of audio files being processed. The service returns a 201 response
    #   code if the audio is valid. It then asynchronously analyzes the contents of the
    #   audio file or files and automatically extracts information about the audio such as
    #   its length, sampling rate, and encoding. You cannot submit requests to train or
    #   upgrade the model until the service's analysis of all audio resources for current
    #   requests completes.
    #
    #   To determine the status of the service's analysis of the audio, use the [Get an
    #   audio resource](#getaudio) method to poll the status of the audio. The method
    #   accepts the customization ID of the custom model and the name of the audio
    #   resource, and it returns the status of the resource. Use a loop to check the
    #   status of the audio every few seconds until it becomes `ok`.
    #
    #   **Note:** Acoustic model customization is supported only for use with
    #   previous-generation models. It is not supported for next-generation models.
    #
    #   **See also:** [Add audio to the custom acoustic
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-acoustic#addAudio).
    #
    #
    #   ### Content types for audio-type resources
    #
    #    You can add an individual audio file in any format that the service supports for
    #   speech recognition. For an audio-type resource, use the `Content-Type` parameter
    #   to specify the audio format (MIME type) of the audio file, including specifying
    #   the sampling rate, channels, and endianness where indicated.
    #   * `audio/alaw` (Specify the sampling rate (`rate`) of the audio.)
    #   * `audio/basic` (Use only with narrowband models.)
    #   * `audio/flac`
    #   * `audio/g729` (Use only with narrowband models.)
    #   * `audio/l16` (Specify the sampling rate (`rate`) and optionally the number of
    #   channels (`channels`) and endianness (`endianness`) of the audio.)
    #   * `audio/mp3`
    #   * `audio/mpeg`
    #   * `audio/mulaw` (Specify the sampling rate (`rate`) of the audio.)
    #   * `audio/ogg` (The service automatically detects the codec of the input audio.)
    #   * `audio/ogg;codecs=opus`
    #   * `audio/ogg;codecs=vorbis`
    #   * `audio/wav` (Provide audio with a maximum of nine channels.)
    #   * `audio/webm` (The service automatically detects the codec of the input audio.)
    #   * `audio/webm;codecs=opus`
    #   * `audio/webm;codecs=vorbis`
    #
    #   The sampling rate of an audio file must match the sampling rate of the base model
    #   for the custom model: for broadband models, at least 16 kHz; for narrowband
    #   models, at least 8 kHz. If the sampling rate of the audio is higher than the
    #   minimum required rate, the service down-samples the audio to the appropriate rate.
    #   If the sampling rate of the audio is lower than the minimum required rate, the
    #   service labels the audio file as `invalid`.
    #
    #    **See also:** [Supported audio
    #   formats](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-audio-formats).
    #
    #
    #   ### Content types for archive-type resources
    #
    #    You can add an archive file (**.zip** or **.tar.gz** file) that contains audio
    #   files in any format that the service supports for speech recognition. For an
    #   archive-type resource, use the `Content-Type` parameter to specify the media type
    #   of the archive file:
    #   * `application/zip` for a **.zip** file
    #   * `application/gzip` for a **.tar.gz** file.
    #
    #   When you add an archive-type resource, the `Contained-Content-Type` header is
    #   optional depending on the format of the files that you are adding:
    #   * For audio files of type `audio/alaw`, `audio/basic`, `audio/l16`, or
    #   `audio/mulaw`, you must use the `Contained-Content-Type` header to specify the
    #   format of the contained audio files. Include the `rate`, `channels`, and
    #   `endianness` parameters where necessary. In this case, all audio files contained
    #   in the archive file must have the same audio format.
    #   * For audio files of all other types, you can omit the `Contained-Content-Type`
    #   header. In this case, the audio files contained in the archive file can have any
    #   of the formats not listed in the previous bullet. The audio files do not need to
    #   have the same format.
    #
    #   Do not use the `Contained-Content-Type` header when adding an audio-type resource.
    #
    #
    #   ### Naming restrictions for embedded audio files
    #
    #    The name of an audio file that is contained in an archive-type resource can
    #   include a maximum of 128 characters. This includes the file extension and all
    #   elements of the name (for example, slashes).
    # @param customization_id [String] The customization ID (GUID) of the custom acoustic model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @param audio_name [String] The name of the new audio resource for the custom acoustic model. Use a localized
    #   name that matches the language of the custom model and reflects the contents of
    #   the resource.
    #   * Include a maximum of 128 characters in the name.
    #   * Do not use characters that need to be URL-encoded. For example, do not use
    #   spaces, slashes, backslashes, colons, ampersands, double quotes, plus signs,
    #   equals signs, questions marks, and so on in the name. (The service does not
    #   prevent the use of these characters. But because they must be URL-encoded wherever
    #   used, their use is strongly discouraged.)
    #   * Do not use the name of an audio resource that has already been added to the
    #   custom model.
    # @param audio_resource [File] The audio resource that is to be added to the custom acoustic model, an individual
    #   audio file or an archive file.
    #
    #   With the `curl` command, use the `--data-binary` option to upload the file for the
    #   request.
    # @param content_type [String] For an audio-type resource, the format (MIME type) of the audio. For more
    #   information, see **Content types for audio-type resources** in the method
    #   description.
    #
    #   For an archive-type resource, the media type of the archive file. For more
    #   information, see **Content types for archive-type resources** in the method
    #   description.
    # @param contained_content_type [String] _For an archive-type resource_, specify the format of the audio files that are
    #   contained in the archive file if they are of type `audio/alaw`, `audio/basic`,
    #   `audio/l16`, or `audio/mulaw`. Include the `rate`, `channels`, and `endianness`
    #   parameters where necessary. In this case, all audio files that are contained in
    #   the archive file must be of the indicated type.
    #
    #   For all other audio formats, you can omit the header. In this case, the audio
    #   files can be of multiple types as long as they are not of the types listed in the
    #   previous paragraph.
    #
    #   The parameter accepts all of the audio formats that are supported for use with
    #   speech recognition. For more information, see **Content types for audio-type
    #   resources** in the method description.
    #
    #   _For an audio-type resource_, omit the header.
    # @param allow_overwrite [Boolean] If `true`, the specified audio resource overwrites an existing audio resource with
    #   the same name. If `false`, the request fails if an audio resource with the same
    #   name already exists. The parameter has no effect if an audio resource with the
    #   same name does not already exist.
    # @return [nil]
    def add_audio(customization_id:, audio_name:, audio_resource:, content_type: nil, contained_content_type: nil, allow_overwrite: nil)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      raise ArgumentError.new("audio_name must be provided") if audio_name.nil?

      raise ArgumentError.new("audio_resource must be provided") if audio_resource.nil?

      headers = {
        "Content-Type" => content_type,
        "Contained-Content-Type" => contained_content_type
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "add_audio")
      headers.merge!(sdk_headers)

      params = {
        "allow_overwrite" => allow_overwrite
      }

      data = audio_resource

      method_url = "/v1/acoustic_customizations/%s/audio/%s" % [ERB::Util.url_encode(customization_id), ERB::Util.url_encode(audio_name)]

      request(
        method: "POST",
        url: method_url,
        headers: headers,
        params: params,
        data: data,
        accept_json: true
      )
      nil
    end

    ##
    # @!method get_audio(customization_id:, audio_name:)
    # Get an audio resource.
    # Gets information about an audio resource from a custom acoustic model. The method
    #   returns an `AudioListing` object whose fields depend on the type of audio resource
    #   that you specify with the method's `audio_name` parameter:
    #   * _For an audio-type resource_, the object's fields match those of an
    #   `AudioResource` object: `duration`, `name`, `details`, and `status`.
    #   * _For an archive-type resource_, the object includes a `container` field whose
    #   fields match those of an `AudioResource` object. It also includes an `audio`
    #   field, which contains an array of `AudioResource` objects that provides
    #   information about the audio files that are contained in the archive.
    #
    #   The information includes the status of the specified audio resource. The status is
    #   important for checking the service's analysis of a resource that you add to the
    #   custom model.
    #   * _For an audio-type resource_, the `status` field is located in the
    #   `AudioListing` object.
    #   * _For an archive-type resource_, the `status` field is located in the
    #   `AudioResource` object that is returned in the `container` field.
    #
    #   You must use credentials for the instance of the service that owns a model to list
    #   its audio resources.
    #
    #   **Note:** Acoustic model customization is supported only for use with
    #   previous-generation models. It is not supported for next-generation models.
    #
    #   **See also:** [Listing audio resources for a custom acoustic
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageAudio#listAudio).
    # @param customization_id [String] The customization ID (GUID) of the custom acoustic model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @param audio_name [String] The name of the audio resource for the custom acoustic model.
    # @return [IBMCloudSdkCore::DetailedResponse] A `IBMCloudSdkCore::DetailedResponse` object representing the response.
    def get_audio(customization_id:, audio_name:)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      raise ArgumentError.new("audio_name must be provided") if audio_name.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "get_audio")
      headers.merge!(sdk_headers)

      method_url = "/v1/acoustic_customizations/%s/audio/%s" % [ERB::Util.url_encode(customization_id), ERB::Util.url_encode(audio_name)]

      response = request(
        method: "GET",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      response
    end

    ##
    # @!method delete_audio(customization_id:, audio_name:)
    # Delete an audio resource.
    # Deletes an existing audio resource from a custom acoustic model. Deleting an
    #   archive-type audio resource removes the entire archive of files. The service does
    #   not allow deletion of individual files from an archive resource.
    #
    #   Removing an audio resource does not affect the custom model until you train the
    #   model on its updated data by using the [Train a custom acoustic
    #   model](#trainacousticmodel) method. You can delete an existing audio resource from
    #   a model while a different resource is being added to the model. You must use
    #   credentials for the instance of the service that owns a model to delete its audio
    #   resources.
    #
    #   **Note:** Acoustic model customization is supported only for use with
    #   previous-generation models. It is not supported for next-generation models.
    #
    #   **See also:** [Deleting an audio resource from a custom acoustic
    #   model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-manageAudio#deleteAudio).
    # @param customization_id [String] The customization ID (GUID) of the custom acoustic model that is to be used for
    #   the request. You must make the request with credentials for the instance of the
    #   service that owns the custom model.
    # @param audio_name [String] The name of the audio resource for the custom acoustic model.
    # @return [nil]
    def delete_audio(customization_id:, audio_name:)
      raise ArgumentError.new("customization_id must be provided") if customization_id.nil?

      raise ArgumentError.new("audio_name must be provided") if audio_name.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "delete_audio")
      headers.merge!(sdk_headers)

      method_url = "/v1/acoustic_customizations/%s/audio/%s" % [ERB::Util.url_encode(customization_id), ERB::Util.url_encode(audio_name)]

      request(
        method: "DELETE",
        url: method_url,
        headers: headers,
        accept_json: true
      )
      nil
    end
    #########################
    # User data
    #########################

    ##
    # @!method delete_user_data(customer_id:)
    # Delete labeled data.
    # Deletes all data that is associated with a specified customer ID. The method
    #   deletes all data for the customer ID, regardless of the method by which the
    #   information was added. The method has no effect if no data is associated with the
    #   customer ID. You must issue the request with credentials for the same instance of
    #   the service that was used to associate the customer ID with the data. You
    #   associate a customer ID with data by passing the `X-Watson-Metadata` header with a
    #   request that passes the data.
    #
    #   **Note:** If you delete an instance of the service from the service console, all
    #   data associated with that service instance is automatically deleted. This includes
    #   all custom language models, corpora, grammars, and words; all custom acoustic
    #   models and audio resources; all registered endpoints for the asynchronous HTTP
    #   interface; and all data related to speech recognition requests.
    #
    #   **See also:** [Information
    #   security](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-information-security#information-security).
    # @param customer_id [String] The customer ID for which all data is to be deleted.
    # @return [nil]
    def delete_user_data(customer_id:)
      raise ArgumentError.new("customer_id must be provided") if customer_id.nil?

      headers = {
      }
      sdk_headers = Common.new.get_sdk_headers("speech_to_text", "V1", "delete_user_data")
      headers.merge!(sdk_headers)

      params = {
        "customer_id" => customer_id
      }

      method_url = "/v1/user_data"

      request(
        method: "DELETE",
        url: method_url,
        headers: headers,
        params: params,
        accept_json: false
      )
      nil
    end
  end
end