class_docstr: A class for tracking BLEU (https://www.aclweb.org/anthology/P02-1040.pdf).
  Arguments
  ---------
  merge_words: bool
      Whether to merge the successive words to create sentences.
  Example
  -------
  >>> bleu = BLEUStats()
  >>> i2l = {0: 'a', 1: 'b'}
  >>> bleu.append(
  ...     ids=['utterance1'],
  ...     predict=[[0, 1, 1]],
  ...     targets=[[[0, 1, 0]], [[0, 1, 1]], [[1, 1, 0]]],
  ...     ind2lab=lambda batch: [[i2l[int(x)] for x in seq] for seq in batch],
  ... )
  >>> stats = bleu.summarize()
  >>> stats['BLEU']
  0.0
code: def __init__(self, lang="en", merge_words=True, max_ngram_order=4):
      # Check extra-dependency for computing the bleu score
      try:
          from sacrebleu.metrics import BLEU
      except ImportError:
          print(
              "Please install sacrebleu (https://pypi.org/project/sacrebleu/) in order to use the BLEU metric"
          )
  
      self.clear()
      self.merge_words = merge_words
      self.bleu = BLEU(max_ngram_order=max_ngram_order)
  
      self.predicts = []
      self.targets = None
  
imports: from speechbrain.utils.metric_stats import MetricStats
label_desc: Use image node_id 1 to create a new BLEUStats object from inherited base classes: MetricStats with example: obj = BLEUStats(lang, merge_words, max_ngram_order)