class_docstr: A class for tracking error rates (e.g., WER, PER).
  
  Arguments
  ---------
  merge_tokens : bool
      Whether to merge the successive tokens (used for e.g.,
      creating words out of character tokens).
      See ``speechbrain.dataio.dataio.merge_char``.
  split_tokens : bool
      Whether to split tokens (used for e.g. creating
      characters out of word tokens).
      See ``speechbrain.dataio.dataio.split_word``.
  space_token : str
      The character to use for boundaries. Used with ``merge_tokens``
      this represents character to split on after merge.
      Used with ``split_tokens`` the sequence is joined with
      this token in between, and then the whole sequence is split.
  keep_values : bool
      Whether to keep the values of the concepts or not.
  extract_concepts_values : bool
      Process the predict and target to keep only concepts and values.
  tag_in : str
      Start of the concept ('<' for exemple).
  tag_out : str
      End of the concept ('>' for exemple).
  
  Example
  -------
  >>> cer_stats = ErrorRateStats()
  >>> i2l = {0: 'a', 1: 'b'}
  >>> cer_stats.append(
  ...     ids=['utterance1'],
  ...     predict=torch.tensor([[0, 1, 1]]),
  ...     target=torch.tensor([[0, 1, 0]]),
  ...     target_len=torch.ones(1),
  ...     ind2lab=lambda batch: [[i2l[int(x)] for x in seq] for seq in batch],
  ... )
  >>> stats = cer_stats.summarize()
  >>> stats['WER']
  33.33...
  >>> stats['insertions']
  0
  >>> stats['deletions']
  0
  >>> stats['substitutions']
  1
docstr: Summarize the error_rate and return relevant statistics.
  
  * See MetricStats.summarize()
docstr_tok: ["Summarize","the","error_rate","and","return","relevant","statistics",".","*","See","MetricStats.summarize","(",")"]
code: def summarize(self, field=None):
      """Summarize the error_rate and return relevant statistics.
  
      * See MetricStats.summarize()
      """
      self.summary = wer_summary(self.scores)
  
      # Add additional, more generic key
      self.summary["error_rate"] = self.summary["WER"]
  
      if field is not None:
          return self.summary[field]
      else:
          return self.summary
  
imports: import torch
  from joblib import Parallel, delayed
  from speechbrain.utils.data_utils import undo_padding
  from speechbrain.utils.edit_distance import wer_summary, wer_details_for_batch
  from speechbrain.dataio.dataio import merge_char, split_word, extract_concepts_values
  from speechbrain.dataio.wer import print_wer_summary, print_alignments
label_desc: Use image node_id 3 for calling the ErrorRateStats obj's underlying member method code with example usage: obj.summarize(field) and returns: self, self