code: def process_audio_default(
      sig,
      norm=True,
      trim=True,
      highpass=True,
      src_sample_rate=48000,
      tgt_sample_rate=22050,
      trim_threshold=-30.0,
  ):
      """Standard audio preprocessing / conversion
  
      Arguments
      ---------
      norm: True
          whether to normalize
      trim: True
          whether to trim silence at the beginning and at the end
      src_sample_rate: int
          the sample rate at which the files are recorded
      tgt_sample_rate: int
          the target sample rate
      trim_threshold: float
          the decibels threshold for trimming the file
      """
      # Resample
      if src_sample_rate != tgt_sample_rate:
          sig = F.resample(sig, src_sample_rate, tgt_sample_rate)
      # VAD
      if trim:
          sig = trim_sig(sig, trim_threshold)
  
      # High pass filter (> 70 Hz)
      if highpass:
          effects = [["highpass", "-2", "70"]]
          sig, _ = torchaudio.sox_effects.apply_effects_tensor(
              sig.unsqueeze(0),
              tgt_sample_rate,
              effects,
              channels_first=True,
          )
          sig = sig.squeeze(0)
  
      # Normalize
      if norm:
          sig = sig / sig.abs().max()
      return sig
  
imports: import logging
  import csv
  import math
  import json
  import os
  import torchaudio
  import speechbrain
  from glob import glob
  from functools import partial
  from tqdm.auto import tqdm
  from torchaudio import functional
  from subprocess import list2cmdline
  from speechbrain.utils.superpowers import run_shell
  from speechbrain.utils.data_utils import download_file
  from speechbrain.dataio.dataio import load_pkl, save_pkl
label_desc: Use image node_id 21 for calling a global function with example usage: process_audio_default(sig, norm, trim, highpass, src_sample_rate, tgt_sample_rate, trim_threshold) and returns: sig