code: def __process_transcript(file_path: str):
      # Create zh-TW to zh-simplify converter
      cc = OpenCC("t2s")
      # Create normalizer
      text_normalizer = Normalizer(
          lang="zh",
          input_case="cased",
          overwrite_cache=True,
          cache_dir=str(file_path / "cache_dir"),
      )
      text_normalizer_call_kwargs = {
          "punct_pre_process": True,
          "punct_post_process": True,
      }
      normalizer_call = lambda x: text_normalizer.normalize(
          x, **text_normalizer_call_kwargs
      )
      entries = []
      i = 0
      with open(file_path / "text_SF.txt", encoding="utf-8") as fin:
          for line in fin:
              content = line.split()
              wav_name, text = content[0], "".join(content[1:])
              wav_name = wav_name.replace("\ufeff", "")
              # WAR: change DL to SF, e.g. real wave file com_SF_ce2727.wav, wav name in text_SF
              # com_DL_ce2727. It would be fixed through the dataset in the future.
              wav_name = wav_name.replace("DL", "SF")
              wav_file = file_path / "wavs" / (wav_name + ".wav")
              assert os.path.exists(wav_file), f"{wav_file} not found!"
              duration = subprocess.check_output(
                  f"soxi -D {wav_file}", shell=True
              )
              simplified_text = cc.convert(text)
              normalized_text = normalizer_call(simplified_text)
              entry = {
                  "audio_filepath": os.path.abspath(wav_file),
                  "duration": float(duration),
                  "text": text,
                  "normalized_text": normalized_text,
              }
  
              i += 1
              entries.append(entry)
      return entries
  
file_path: NeMo/scripts/dataset_processing/tts/sfbilingual/get_data.py
imports: import argparse
  import json
  import os
  import random
  import subprocess
  from pathlib import Path
  import numpy
  from opencc import OpenCC
label_desc: Use image node_id 2 for calling a global function with example usage: __process_transcript(file_path) and returns: entries