class_docstr: Representation of an individual segment in an STM file.
class_docstr_tok: ["Representation","of","an","individual","segment","in","an","STM","file","."]
code: def __init__(self, stm_line):
      tokens = stm_line.split()
      self._filename = tokens[0]
      self._channel = tokens[1]
      self._speaker_id = tokens[2]
      self._start_time = float(tokens[3])
      self._stop_time = float(tokens[4])
      self._labels = tokens[5]
      self._transcript = ""
      for token in tokens[6:]:
          self._transcript += token + " "
      # We need to do the encode-decode dance here because encode
      # returns a bytes() object on Python 3, and text_to_char_array
      # expects a string.
      self._transcript = (
          unicodedata.normalize("NFKD", self._transcript.strip())
          .encode("ascii", "ignore")
          .decode("ascii", "ignore")
      )
  
file_path: DeepSpeech/training/deepspeech_training/util/stm.py
imports: import codecs
  import unicodedata
label_desc: Use image node_id 1 to create a new STMSegment object from inherited base classes: object with example: obj = STMSegment(stm_line)