code: def prepare_json(
      json_file,
      src_audio_folder,
      tgt_audio_folder,
      src_validated,
      tgt_split,
      limit_to_n_sample=None,
  ):
      """
      Creates json file.
  
      """
  
      json_dict = {}
      tgt_meta = list(
          csv.reader(
              open(tgt_split), delimiter="\t", quoting=csv.QUOTE_NONE
          )
      )
  
      limit_to_n_sample = (
          len(tgt_meta) if not limit_to_n_sample else limit_to_n_sample
      )
  
      for i in tqdm.tqdm(range(limit_to_n_sample)):
          session_id = tgt_meta[i][0].split(".")[0]
  
          tgt_audio = f"{tgt_audio_folder}/{session_id}.mp3.wav"
          src_audio = f"{src_audio_folder}/{session_id}.mp3"
  
          src_sig, sr = torchaudio.load(src_audio)
          duration = src_sig.shape[1] / sr
  
          # src_text = meta_dict[session_id]["sentence"]
          tgt_text = tgt_meta[i][1]
  
          if duration < 1.5 or len(tgt_text) < 10:
              continue
  
          json_dict[session_id] = {
              "src_audio": src_audio,
              "tgt_audio": tgt_audio,
              "duration": duration,
              # "src_text": src_text,
              "tgt_text": tgt_text,
          }
  
      # Writing the dictionary to the json file
      with open(json_file, mode="w") as json_f:
          json.dump(json_dict, json_f, indent=2)
  
      logger.info(f"{json_file} successfully created!")
  
file_path: speechbrain/recipes/CVSS/cvss_prepare.py
imports: import os
  import csv
  import json
  import logging
  import random
  import tqdm
  import pathlib
  import torchaudio
  from speechbrain.dataio.dataio import load_pkl, save_pkl
label_desc: Use image node_id 3 for calling a global function with example usage: prepare_json(json_file, src_audio_folder, tgt_audio_folder, src_validated, tgt_split, limit_to_n_sample) without return types