code: def process(x: dict) -> dict:
      if not isinstance(x[FIELD_TEXT], str):
          x[FIELD_TEXT] = ""
      else:
          x[FIELD_TEXT] = x[FIELD_TEXT].lower().strip()
  
      data_dir = x[FIELD_DATA_DIR]
      input_file = Path(x[FIELD_AUDIO])
      if not input_file.is_absolute():
          input_file_path = str(data_dir / input_file)
      else:
          input_file_path = str(input_file)
  
      output_file = Path(input_file.stem + ".wav")
  
      if "slurp_real" in input_file_path:
          output_dir = Path("wavs/slurp_real")
      else:
          output_dir = Path("wavs/slurp_synth")
  
      output_file_path = str(data_dir / output_dir / output_file)
  
      if not os.path.exists(output_file_path):
          y, _ = librosa.load(input_file_path, sr=sampling_rate)
          sf.write(output_file_path, y, sampling_rate)
  
      y, _ = librosa.load(output_file_path, sr=sampling_rate)
      x["duration"] = librosa.get_duration(y=y, sr=sampling_rate)
      x[FIELD_AUDIO] = str(output_dir / output_file)
      del x[FIELD_DATA_DIR]
      return x
  
file_path: NeMo/scripts/dataset_processing/process_slurp_data.py
imports: import argparse
  import json
  import multiprocessing
  import os
  import tarfile
  from pathlib import Path
  import librosa
  import pandas
  import soundfile
  import wget
  from tqdm import tqdm
  from tqdm.contrib.concurrent import process_map
label_desc: Use image node_id 5 for calling a global function with example usage: process(x) and returns: x