code: def create_sets(data_folder, extension):
      """
      Creates lists for train, dev and test sets with data from the data_folder
  
      Arguments
      ---------
      data_folder : str
          Path of the CommonLanguage dataset.
      extension: list of file extentions
          List of strings with file extentions that correspond to the audio files
          in the CommonLanguage dataset
  
      Returns
      -------
      dictionary containing train, dev, and test splits.
      """
  
      # Datasets initialization
      datasets = {"train", "dev", "test"}
      data_split = {dataset: [] for dataset in datasets}
  
      # Get the list of languages from the dataset folder
      languages = [
          name
          for name in os.listdir(data_folder)
          if os.path.isdir(os.path.join(data_folder, name))
          and datasets.issubset(
              os.listdir(os.path.join(data_folder, name))
          )
      ]
  
      msg = f"{len(languages)} languages detected!"
      logger.info(msg)
  
      # Fill the train, dev and test datasets with audio filenames
      for language in languages:
          for dataset in datasets:
              curr_folder = os.path.join(data_folder, language, dataset)
              wav_list = get_all_files(curr_folder, match_and=extension)
              data_split[dataset].extend(wav_list)
  
      msg = "Data successfully split!"
      logger.info(msg)
  
      return data_split
  
file_path: speechbrain/recipes/CommonLanguage/common_language_prepare.py
imports: import os
  import csv
  import logging
  import torchaudio
  from tqdm.contrib import tzip
  from speechbrain.utils.data_utils import get_all_files
label_desc: Use image node_id 3 for calling a global function with example usage: create_sets(data_folder, extension) and returns: data_split