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 _load_audio(self, file_path) -> Tuple[Tensor, int]:
      return torchaudio.load(file_path)
  
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 3 for calling the VCTK_092 obj's underlying member method code with example usage: obj._load_audio(file_path) and returns: torchaudio