code: def collate_wrapper(batch):
      speeches, labels = [], []
      for speech, _, label, _, _, _ in batch:
          speeches.append(speech)
          labels.append(label.strip().lower().strip())
      return speeches, labels
  
file_path: audio/examples/asr/librispeech_cuda_ctc_decoder/inference.py
imports: import argparse
  import logging
  import time
  import sentencepiece
  import torch
  import torchaudio
  from torch.nn.utils.rnn import pad_sequence
  from torch.utils.data import DataLoader
  from torchaudio.models.decoder import ctc_decoder, cuda_ctc_decoder
label_desc: Use image node_id 1 for calling a global function with example usage: collate_wrapper(batch) and returns: speeches,  labels