old_contents: from collections import Counter
  from textgrid import TextGrid, IntervalTier
  from .aligner import AlignerParser
  
  from polyglotdb.io.parsers.speaker import FilenameSpeakerParser
  
  
  class LabbCatParser(AlignerParser):
      name = 'LabbCat'
      word_label = 'orthography'
      phone_label = 'segment'
      speaker_first = False
  
      def __init__(self, annotation_tiers, hierarchy, make_transcription=True,
                   stop_check=None, call_back=None):
          super(AlignerParser, self).__init__(annotation_tiers, hierarchy, make_transcription,
                                          False, stop_check, call_back)
          self.speaker_parser = FilenameSpeakerParser(0)
  
      def load_textgrid(self, path):
          tg = TextGrid(strict=False)
          try:
              tg.read(path)
              new_tiers = []
              dup_tiers_maxes = {k:0 for k,v in Counter([t.name for t in tg.tiers]).items() if v > 1}
              dup_tiers_inds = {k:0 for k in dup_tiers_maxes.keys()}
  
              for i, t in enumerate(tg.tiers):
                  if t.name in dup_tiers_maxes:
                      if len(t) > dup_tiers_maxes[t.name]:
                          dup_tiers_maxes[t.name] = len(t)
                          dup_tiers_inds[t.name] = i
              for i, t in enumerate(tg.tiers):
                  if t.name in dup_tiers_maxes:
                      if i != dup_tiers_inds[t.name]:
                          continue
                  new_tiers.append(t)
              tg.tiers = new_tiers
              return tg
          except Exception as e:
              print('There was an issue parsing {}:'.format(path))
              raise
  
new_contents: from collections import Counter
  from textgrid import TextGrid, IntervalTier
  from .aligner import AlignerParser
  
  from polyglotdb.io.parsers.speaker import FilenameSpeakerParser
  
  
  class LabbCatParser(AlignerParser):
      name = 'LabbCat'
      word_label = 'transcript'
      phone_label = 'segment'
      speaker_first = False
  
      def __init__(self, annotation_tiers, hierarchy, make_transcription=True,
                   stop_check=None, call_back=None):
          super(AlignerParser, self).__init__(annotation_tiers, hierarchy, make_transcription,
                                          False, stop_check, call_back)
          self.speaker_parser = FilenameSpeakerParser(0)
  
      def load_textgrid(self, path):
          tg = TextGrid(strict=False)
          try:
              tg.read(path)
              new_tiers = []
              dup_tiers_maxes = {k:0 for k,v in Counter([t.name for t in tg.tiers]).items() if v > 1}
              dup_tiers_inds = {k:0 for k in dup_tiers_maxes.keys()}
  
              for i, t in enumerate(tg.tiers):
                  if t.name in dup_tiers_maxes:
                      if len(t) > dup_tiers_maxes[t.name]:
                          dup_tiers_maxes[t.name] = len(t)
                          dup_tiers_inds[t.name] = i
              for i, t in enumerate(tg.tiers):
                  if t.name in dup_tiers_maxes:
                      if i != dup_tiers_inds[t.name]:
                          continue
                  new_tiers.append(t)
              tg.tiers = new_tiers
              return tg
          except Exception as e:
              print('There was an issue parsing {}:'.format(path))
              raise
  
subject: Revert LaBB-CAT parser to use transcript tier