code: def __process_utterance(
      file_id, trans_path, line, keep_low_conf, rem_noises, emojify
  ):
      """
      Processes one utterance (one line of a transcript).
      Args:
          file_id: the ID of the transcript file
          trans_path: transcript path
          line: one line in the transcript file
          keep_low_conf: whether to keep low confidence lines
          rem_noises: whether to remove noise symbols
          emojify: whether to convert noise symbols to emoji, lower precedence
      """
      # Check for lines to skip (comments, empty, low confidence)
      if (
          line.startswith("#")
          or not line.strip()
          or (not keep_low_conf and "((" in line)
      ):
          return None, None, None, None
  
      # Data and sanity checks
      line = line.split()
  
      t_start, t_end = float(line[0]), float(line[1])
      if (t_start < 0) or (t_end < t_start):
          print(f"Invalid time: {t_start} to {t_end} in {trans_path}")
          return None, None, None, None
  
      channel = line[2]
      idx = 0 if line[2] == "A:" else 1
  
      if channel not in ("A:", "B:"):
          print(
              f"Could not read channel info ({channel}) in {trans_path}"
          )
          return None, None, None, None
  
      # Replacements as necessary
      line_id = "-".join(
          [file_id, channel[0], str(t_start * 10), str(t_end * 10)]
      )
  
      content = TRANSCRIPT_BUGS.get(line_id, " ".join(line[3:]))
  
      if content is None:
          return None, None, None, None
  
      for tag, newtag in TRANSCRIPT_NUMBERS.items():
          content = content.replace(tag, newtag)
  
      content = __normalize(content)
  
      if rem_noises:
          for k, _ in TAG_MAP.items():
              content = content.replace(k, "")
      elif emojify:
          for k, v in TAG_MAP.items():
              content = content.replace(k, v)
  
      return t_start, t_end, idx, content
  
file_path: NeMo/scripts/dataset_processing/process_fisher_data.py
imports: import argparse
  import glob
  import json
  import os
  import re
  from math import ceil, floor
  import numpy
  import scipy.io.wavfile
  from tqdm import tqdm
label_desc: Use image node_id 3 for calling a global function with example usage: __process_utterance(file_id, trans_path, line, keep_low_conf, rem_noises, emojify) and returns: t_start,  t_end,  idx,  content, None,  None,  None,  None, None,  None,  None,  None, None,  None,  None,  None, None,  None,  None,  None