code: def __process_data(data_folder: str, dst_folder: str):
      """
      To generate manifest
      Args:
          data_folder: source with wav files
          dst_folder: where manifest files will be stored
      Returns:
  
      """
  
      if not os.path.exists(dst_folder):
          os.makedirs(dst_folder)
  
      transcript_file = os.path.join(
          data_folder, "transcript", "aishell_transcript_v0.8.txt"
      )
      transcript_dict = {}
      with open(transcript_file, "r", encoding="utf-8") as f:
          for line in f:
              line = line.strip()
              audio_id, text = line.split(" ", 1)
              # remove white space
              text = text.replace(" ", "")
              transcript_dict[audio_id] = text
  
      data_types = ["train", "dev", "test"]
      vocab_count = {}
      for dt in data_types:
          json_lines = []
          audio_dir = os.path.join(data_folder, "wav", dt)
          for sub_folder, _, file_list in os.walk(audio_dir):
              for fname in file_list:
                  audio_path = os.path.join(sub_folder, fname)
                  audio_id = fname.strip(".wav")
                  if audio_id not in transcript_dict:
                      continue
                  text = transcript_dict[audio_id]
                  for li in text:
                      vocab_count[li] = vocab_count.get(li, 0) + 1
                  duration = subprocess.check_output(
                      "soxi -D {0}".format(audio_path), shell=True
                  )
                  duration = float(duration)
                  json_lines.append(
                      json.dumps(
                          {
                              "audio_filepath": os.path.abspath(
                                  audio_path
                              ),
                              "duration": duration,
                              "text": text,
                          },
                          ensure_ascii=False,
                      )
                  )
  
          manifest_path = os.path.join(dst_folder, dt + ".json")
          with open(manifest_path, "w", encoding="utf-8") as fout:
              for line in json_lines:
                  fout.write(line + "\n")
  
      vocab = sorted(
          vocab_count.items(), key=lambda k: k[1], reverse=True
      )
      vocab_file = os.path.join(dst_folder, "vocab.txt")
      with open(vocab_file, "w", encoding="utf-8") as f:
          for v, c in vocab:
              f.write(v + "\n")
  
file_path: NeMo/scripts/dataset_processing/get_aishell_data.py
imports: import argparse
  import json
  import logging
  import os
  import subprocess
  import tarfile
  import urllib.request
  from tqdm import tqdm
label_desc: Use image node_id 5 for calling a global function with example usage: __process_data(data_folder, dst_folder) without return types