code: def process_line(
      talk_sph,
      avoid_if_shorter_than,
      utt_save_folder_split,
      data_folder,
      split,
  ):
      """This function processes a single Ted-talk recording.
  
      Arguments
      ---------
      talk_sph : str
          The name of the Ted-talk recording.
      avoid_if_shorter_than: int
          Any utterance shorter than this will be discarded.
      utt_save_folder_split: str
          The folder stores the clipped individual utterences.
      data_folder: str
          The folder stores the original Ted-talk recordings.
      split: str
          The split of the dataset, e.g., train, dev, test.
      """
      talk_name = talk_sph[:-4]
      talk_sph_path = os.path.join(data_folder, split, "sph", talk_sph)
      talk_stm_path = os.path.join(
          data_folder, split, "stm", talk_name + ".stm"
      )
  
      return make_splits(
          talk_sph_path,
          talk_stm_path,
          utt_save_folder_split,
          avoid_if_shorter_than,
      )
  
file_path: speechbrain/recipes/Tedlium2/Tokenizer/tedlium2_prepare.py
imports: import os
  import csv
  import logging
  import torchaudio
  import functools
  from speechbrain.utils.parallel import parallel_map
label_desc: Use image node_id 2 for calling a global function with example usage: process_line(talk_sph, avoid_if_shorter_than, utt_save_folder_split, data_folder, split) and returns: make_splits