code: def prepare_musan(
      folder, music_csv, noise_csv, speech_csv, max_noise_len=None
  ):
      """Prepare the musan dataset (music, noise, speech).
  
      Arguments
      ---------
      folder : str
          The location of the folder containing the dataset.
      noise_csv : str
          Filename for storing the prepared noise csv.
      max_noise_len : float
          The maximum noise length in seconds. Noises longer
          than this will be cut into pieces.
      """
  
      sub_folders = ["music", "noise", "speech"]
      csv_files = [music_csv, noise_csv, speech_csv]
      logger.info("Musan Data Preparation...")
      for sub_folder, csv_file in zip(sub_folders, csv_files):
          wav_lst = get_all_files(
              os.path.join(folder, sub_folder), match_and=[".wav"]
          )
          if not os.path.isfile(csv_file):
              logger.info(csv_file + " creation...")
              _prepare_csv(folder, wav_lst, csv_file, max_noise_len)
  
imports: import os
  import logging
  import torchaudio
  import speechbrain
  from speechbrain.utils.data_utils import get_all_files
label_desc: Use image node_id 1 for calling a global function with example usage: prepare_musan(folder, music_csv, noise_csv, speech_csv, max_noise_len) without return types