class_docstr: Augmenter that change loudness on mel spectrogram by random values.
  
  :param tuple zone: Default value is (0.2, 0.8). Assign a zone for augmentation. By default, no any augmentation
       will be applied in first 20% and last 20% of whole audio.
  :param float coverage: Default value is 1 and value should be between 0 and 1. Portion of augmentation. 
      If `1` is assigned, augment operation will be applied to target audio segment. For example, the audio 
      duration is 60 seconds while zone and coverage are (0.2, 0.8) and 0.7 respectively. 42 
      seconds ((0.8-0.2)*0.7*60) audio will be augmented.
  :param tuple factor: Default value is (0.5, 2). Volume change value will be picked within the range of this 
      tuple value. Volume will be reduced if value is between 0 and 1. Otherwise, volume will be increased.
  :param str name: Name of this augmenter
code: def __init__(
      self,
      name="Loudness_Aug",
      zone=(0.2, 0.8),
      coverage=1.0,
      factor=(0.5, 2),
      verbose=0,
      silence=False,
      stateless=True,
  ):
      super().__init__(
          action=Action.SUBSTITUTE,
          zone=zone,
          coverage=coverage,
          factor=factor,
          verbose=verbose,
          name=name,
          silence=silence,
          stateless=stateless,
      )
  
      self.model = nms.Loudness()
  
file_path: nlpaug/nlpaug/augmenter/spectrogram/loudness.py
imports: import numpy
  from nlpaug.augmenter.spectrogram import SpectrogramAugmenter
  from nlpaug.util import Action
  import nlpaug.model.spectrogram
label_desc: Use image node_id 1 to create a new LoudnessAug object from inherited base classes: SpectrogramAugmenter with example: obj = LoudnessAug(name, zone, coverage, factor, verbose, silence, stateless)