code: def _get_noise(
      self, goal_shape, always_2d=False, use_sample_rate=None
  ):
      for i in range(np.random.randint(3, 8)):
          speech = self.pick_sample(
              goal_shape, always_2d, use_sample_rate
          )
          if i == 0:
              agg_noise = speech
          else:  # SNR scaled by i (how many noise signals already in agg_noise)
              agg_noise = self._mix(agg_noise, speech, i)
      return agg_noise
  
imports: from pathlib import Path
  import numpy
  from math import ceil
  from fairseq.data.audio import rand_uniform
  from fairseq.data.audio.waveform_transforms import AudioWaveformTransform, register_audio_waveform_transform
label_desc: Use image node_id 1 for calling the BabbleAugmentTransform obj's underlying member method code with example usage: obj._get_noise(goal_shape, always_2d, use_sample_rate) and returns: agg_noise