code: def __init__(self, root, url, download, subset, mfcc_preprocessing):
      os.makedirs(root, exist_ok=True)
      super().__init__(
          root=root, download=download, subset=subset, url=url
      )
      self.labels_names = [
          "backward",
          "bed",
          "bird",
          "cat",
          "dog",
          "down",
          "eight",
          "five",
          "follow",
          "forward",
          "four",
          "go",
          "happy",
          "house",
          "learn",
          "left",
          "marvin",
          "nine",
          "no",
          "off",
          "on",
          "one",
          "right",
          "seven",
          "sheila",
          "six",
          "stop",
          "three",
          "tree",
          "two",
          "up",
          "visual",
          "wow",
          "yes",
          "zero",
      ]
      self.mfcc_preprocessing = mfcc_preprocessing
  
file_path: avalanche/avalanche/benchmarks/datasets/torchaudio_wrapper.py
imports: import os
  from avalanche.benchmarks.utils import _make_taskaware_classification_dataset
  from avalanche.benchmarks.datasets import default_dataset_location
  import torch
label_desc: Use image node_id 1 to create a new SpeechCommandsData object from inherited base classes: SPEECHCOMMANDS with example: obj = SpeechCommandsData(root, url, download, subset, mfcc_preprocessing)