class_docstr: Task object for CTC segmentation.
  
  When formatted with str(·), this object returns
  results in a kaldi-style segments file formatting.
  The human-readable output can be configured with
  the printing options.
  
  Properties:
      text: Utterance texts, separated by line. But without the utterance
          name at the beginning of the line (as in kaldi-style text).
      ground_truth_mat: Ground truth matrix (CTC segmentation).
      utt_begin_indices: Utterance separator for the Ground truth matrix.
      timings: Time marks of the corresponding chars.
      state_list: Estimated alignment of chars/tokens.
      segments: Calculated segments as: (start, end, confidence score).
      config: CTC Segmentation configuration object.
      name: Name of aligned audio file (Optional). If given, name is
          considered when generating the text.
      utt_ids: The list of utterance names (Optional). This list should
          have the same length as the number of utterances.
      lpz: CTC posterior log probabilities (Optional).
  
  Properties for printing:
      print_confidence_score: Includes the confidence score.
      print_utterance_text: Includes utterance text.
docstr: Return a kaldi-style ``segments`` file (string).
docstr_tok: ["Return","a","kaldi-style","``","segments","``","file","(","string",")","."]
code: def __str__(self):
      """Return a kaldi-style ``segments`` file (string)."""
      output = ""
      num_utts = len(self.segments)
      if self.utt_ids is None:
          utt_names = [f"{self.name}_{i:04}" for i in range(num_utts)]
      else:
          # ensure correct mapping of segments to utterance ids
          assert num_utts == len(self.utt_ids)
          utt_names = self.utt_ids
      for i, boundary in enumerate(self.segments):
          # utterance name and file name
          utt_entry = f"{utt_names[i]} {self.name} "
          # segment start and end
          utt_entry += f"{boundary[0]:.2f} {boundary[1]:.2f}"
          # confidence score
          if self.print_confidence_score:
              utt_entry += f" {boundary[2]:3.4f}"
          # utterance ground truth
          if self.print_utterance_text:
              utt_entry += f" {self.text[i]}"
          output += utt_entry + "\n"
      return output
  
imports: import argparse
  import logging
  import sys
  from pathlib import Path
  from typing import List, Optional, TextIO, Union
  import numpy
  import soundfile
  import torch
  from ctc_segmentation import CtcSegmentationParameters, ctc_segmentation, determine_utterance_segments, prepare_text, prepare_token_list
  from typeguard import check_argument_types, check_return_type
  from espnet2.tasks.asr import ASRTask
  from espnet2.torch_utils.device_funcs import to_device
  from espnet2.utils import config_argparse
  from espnet2.utils.types import str2bool, str_or_none
  from espnet.utils.cli_utils import get_commandline_args
label_desc: Use image node_id 3 for calling the CTCSegmentationTask obj's underlying member method code with example usage: obj.__str__() and returns: output