class_docstr: *VCTK 0.92* :cite:`yamagishi2019vctk` dataset
  
  Args:
      root (str): Root directory where the dataset's top level directory is found.
      mic_id (str, optional): Microphone ID. Either ``"mic1"`` or ``"mic2"``. (default: ``"mic2"``)
      download (bool, optional):
          Whether to download the dataset if it is not found at root path. (default: ``False``).
      url (str, optional): The URL to download the dataset from.
          (default: ``"https://datashare.is.ed.ac.uk/bitstream/handle/10283/3443/VCTK-Corpus-0.92.zip"``)
      audio_ext (str, optional): Custom audio extension if dataset is converted to non-default audio format.
  
  Note:
      * All the speeches from speaker ``p315`` will be skipped due to the lack of the corresponding text files.
      * All the speeches from ``p280`` will be skipped for ``mic_id="mic2"`` due to the lack of the audio files.
      * Some of the speeches from speaker ``p362`` will be skipped due to the lack of  the audio files.
      * See Also: https://datashare.is.ed.ac.uk/handle/10283/3443
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code: def __init__(
      self,
      root: str,
      mic_id: str = "mic2",
      download: bool = False,
      url: str = URL,
      audio_ext=".flac",
  ):
      if mic_id not in ["mic1", "mic2"]:
          raise RuntimeError(
              f'`mic_id` has to be either "mic1" or "mic2". Found: {mic_id}'
          )
  
      archive = os.path.join(root, "VCTK-Corpus-0.92.zip")
  
      self._path = os.path.join(root, "VCTK-Corpus-0.92")
      self._txt_dir = os.path.join(self._path, "txt")
      self._audio_dir = os.path.join(
          self._path, "wav48_silence_trimmed"
      )
      self._mic_id = mic_id
      self._audio_ext = audio_ext
  
      if download:
          if not os.path.isdir(self._path):
              if not os.path.isfile(archive):
                  checksum = _CHECKSUMS.get(url, None)
                  download_url_to_file(
                      url, archive, hash_prefix=checksum
                  )
              _extract_zip(archive, self._path)
  
      if not os.path.isdir(self._path):
          raise RuntimeError(
              "Dataset not found. Please use `download=True` to download it."
          )
  
      # Extracting speaker IDs from the folder structure
      self._speaker_ids = sorted(os.listdir(self._txt_dir))
      self._sample_ids = []
  
      """
          Due to some insufficient data complexity in the 0.92 version of this dataset,
          we start traversing the audio folder structure in accordance with the text folder.
          As some of the audio files are missing of either ``mic_1`` or ``mic_2`` but the
          text is present for the same, we first check for the existence of the audio file
          before adding it to the ``sample_ids`` list.
  
          Once the ``audio_ids`` are loaded into memory we can quickly access the list for
          different parameters required by the user.
          """
      for speaker_id in self._speaker_ids:
          if speaker_id == "p280" and mic_id == "mic2":
              continue
          utterance_dir = os.path.join(self._txt_dir, speaker_id)
          for utterance_file in sorted(
              f for f in os.listdir(utterance_dir) if f.endswith(".txt")
          ):
              utterance_id = os.path.splitext(utterance_file)[0]
              audio_path_mic = os.path.join(
                  self._audio_dir,
                  speaker_id,
                  f"{utterance_id}_{mic_id}{self._audio_ext}",
              )
              if speaker_id == "p362" and not os.path.isfile(
                  audio_path_mic
              ):
                  continue
              self._sample_ids.append(utterance_id.split("_"))
  
file_path: audio/src/torchaudio/datasets/vctk.py
imports: import os
  from typing import Tuple
  import torchaudio
  from torch import Tensor
  from torch.utils.data import Dataset
  from torchaudio._internal import download_url_to_file
  from torchaudio.datasets.utils import _extract_zip
label_desc: Use image node_id 1 to create a new VCTK_092 object from inherited base classes: Dataset with example: obj = VCTK_092(root, mic_id, download, url, audio_ext)