class_docstr: *Device Recorded VCTK (Small subset version)* :cite:`Sarfjoo2018DeviceRV` dataset.
  
  Args:
      root (str or Path): Root directory where the dataset's top level directory is found.
      subset (str): The subset to use. Can be one of ``"train"`` and ``"test"``. (default: ``"train"``).
      download (bool):
          Whether to download the dataset if it is not found at root path. (default: ``False``).
      url (str): The URL to download the dataset from.
          (default: ``"https://datashare.ed.ac.uk/bitstream/handle/10283/3038/DR-VCTK.zip"``)
code: def _load_dr_vctk_item(
      self, filename: str
  ) -> Tuple[Tensor, int, Tensor, int, str, str, str, int]:
      speaker_id, utterance_id = filename.split(".")[0].split("_")
      source, channel_id = self._config[filename]
      file_clean_audio = self._clean_audio_dir / filename
      file_noisy_audio = self._noisy_audio_dir / filename
      waveform_clean, sample_rate_clean = torchaudio.load(
          file_clean_audio
      )
      waveform_noisy, sample_rate_noisy = torchaudio.load(
          file_noisy_audio
      )
      return (
          waveform_clean,
          sample_rate_clean,
          waveform_noisy,
          sample_rate_noisy,
          speaker_id,
          utterance_id,
          source,
          channel_id,
      )
  
file_path: audio/src/torchaudio/datasets/dr_vctk.py
imports: from pathlib import Path
  from typing import Dict, Tuple, Union
  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 DR_VCTK obj's underlying member method code with example usage: obj._load_dr_vctk_item(filename) and returns: waveform_clean,  sample_rate_clean,  waveform_noisy,  sample_rate_noisy,  speaker_id,  utterance_id,  source,  channel_id