code: def compute_word_level_distance(seq1, seq2):
      return torchaudio.functional.edit_distance(
          seq1.lower().split(), seq2.lower().split()
      )
  
file_path: audio/examples/asr/emformer_rnnt/eval.py
imports: import logging
  import pathlib
  from argparse import ArgumentParser, RawTextHelpFormatter
  import torch
  import torchaudio
  from common import MODEL_TYPE_LIBRISPEECH, MODEL_TYPE_MUSTC, MODEL_TYPE_TEDLIUM3
  from librispeech.lightning import LibriSpeechRNNTModule
  from mustc.lightning import MuSTCRNNTModule
  from tedlium3.lightning import TEDLIUM3RNNTModule
label_desc: Use image node_id 1 for calling a global function with example usage: compute_word_level_distance(seq1, seq2) and returns: torchaudio