code: def _maybe_convert_sets(target_dir, extracted_data):
      extracted_dir = os.path.join(target_dir, extracted_data, "wav48")
      txt_dir = os.path.join(target_dir, extracted_data, "txt")
  
      directory = os.path.expanduser(extracted_dir)
      srtd = len(sorted(os.listdir(directory)))
      all_samples = []
  
      for target in sorted(os.listdir(directory)):
          all_samples += _maybe_prepare_set(
              path.join(extracted_dir, os.path.split(target)[-1])
          )
  
      num_samples = len(all_samples)
      print(f"Converting wav files to {SAMPLE_RATE}hz...")
      pool = Pool()
      bar = progressbar.ProgressBar(
          max_value=num_samples, widgets=SIMPLE_BAR
      )
      for i, _ in enumerate(
          pool.imap_unordered(one_sample, all_samples), start=1
      ):
          bar.update(i)
      bar.update(num_samples)
      pool.close()
      pool.join()
  
      _write_csv(extracted_dir, txt_dir, target_dir)
  
file_path: DeepSpeech/bin/import_vctk.py
imports: import os
  import random
  import re
  from multiprocessing import Pool
  from zipfile import ZipFile
  import librosa
  import progressbar
  from deepspeech_training.util.downloader import SIMPLE_BAR, maybe_download
  from deepspeech_training.util.importers import get_counter, get_imported_samples, print_import_report
label_desc: Use image node_id 3 for calling a global function with example usage: _maybe_convert_sets(target_dir, extracted_data) without return types