      model is not trained on new words extracted from corpora.
      - parameter customizationWeight: 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 value is 0.3.   The default value yields the best
+     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

     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 **List a custom language model** 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 `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 corpora or words, until the

     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** 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. But the addition of one audio resource must be
     fully complete before you can add another. You must add a minimum of 10 minutes and a maximum of 50 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 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 add
     additional audio resources to a custom acoustic model, or to train the model, until the service's analysis of all
     audio files for the current request completes.   To determine the status of the service's analysis of the audio,
     use the **List an audio resource** method to poll the status of the audio. The method accepts the GUID 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`.     ###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: *
     `audio/basic` (Use only with narrowband models.) * `audio/flac` * `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`   For information about the
     supported audio formats, including specifying the sampling rate, channels, and endianness for the indicated
     formats, see [Audio formats](https://console.bluemix.net/docs/services/speech-to-text/audio-formats.html).
     **Note:** 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`.
     ###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.   All audio files contained in the archive must have the same
     audio format. Use the `Contained-Content-Type` parameter to specify the format of the contained audio files. The
     parameter accepts all of the audio formats supported for use with speech recognition and with the `Content-Type`
     header, including the `rate`, `channels`, and `endianness` parameters that are used with some formats. The default
     contained audio format is `audio/wav`.

     - parameter customizationID: The GUID of the custom acoustic model. You must make the request with service credentials created for the instance
     of the service that owns the custom model.
     - parameter audioName: The name of the audio resource for the custom acoustic model. When adding an audio resource, do not include spaces
     in the name; use a localized name that matches the language of the custom model.
     - parameter audioResource: The audio resource that is to be added to the custom acoustic model, an individual audio file or an archive file.
     - parameter contentType: The type of the input: application/zip, application/gzip, 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, or audio/webm;codecs=vorbis.
     - parameter containedContentType: For an archive-type resource, specifies the format of the audio files contained in the archive file. The parameter
     accepts all of the audio formats supported for use with speech recognition, including the `rate`, `channels`, and
     `endianness` parameters that are used with some formats. For a complete list of supported audio formats, see [Audio
     formats](/docs/services/speech-to-text/input.html#formats).
     - parameter allowOverwrite: If `true`, the specified corpus or audio resource overwrites an existing corpus or audio resource with the same
     name. If `false` (the default), the request fails if a corpus or audio resource with the same name already exists.
     The parameter has no effect if a corpus or audio resource with the same name does not already exist.
     - parameter failure: A function executed if an error occurs.
     - parameter success: A function executed with the successful result.
     */
