class_docstr: *Tedlium* :cite:`rousseau2012tedlium` dataset (releases 1,2 and 3).
  
  Args:
      root (str or Path): Path to the directory where the dataset is found or downloaded.
      release (str, optional): Release version.
          Allowed values are ``"release1"``, ``"release2"`` or ``"release3"``.
          (default: ``"release1"``).
      subset (str, optional): The subset of dataset to use. Valid options are ``"train"``, ``"dev"``,
          and ``"test"``. Defaults to ``"train"``.
      download (bool, optional):
          Whether to download the dataset if it is not found at root path. (default: ``False``).
      audio_ext (str, optional): extension for audio file (default: ``".sph"``)
docstr: Load the n-th sample from the dataset.
  
  Args:
      n (int): The index of the sample to be loaded
  
  Returns:
      Tuple of the following items;
  
      Tensor:
          Waveform
      int:
          Sample rate
      str:
          Transcript
      int:
          Talk ID
      int:
          Speaker ID
      int:
          Identifier
docstr_tok: ["Load","the","n-th","sample","from","the","dataset",".","Args",":","n","(","int",")",":","The","index","of","the","sample","to","be","loaded","Returns",":","Tuple","of","the","following","items",";","Tensor",":","Waveform","int",":","Sample","rate","str",":","Transcript","int",":","Talk","ID","int",":","Speaker","ID","int",":","Identifier"]
code: def __getitem__(
      self, n: int
  ) -> Tuple[Tensor, int, str, int, int, int]:
      """Load the n-th sample from the dataset.
  
      Args:
          n (int): The index of the sample to be loaded
  
      Returns:
          Tuple of the following items;
  
          Tensor:
              Waveform
          int:
              Sample rate
          str:
              Transcript
          int:
              Talk ID
          int:
              Speaker ID
          int:
              Identifier
      """
      fileid, line = self._filelist[n]
      return self._load_tedlium_item(fileid, line, self._path)
  
file_path: audio/src/torchaudio/datasets/tedlium.py
imports: import os
  from pathlib import Path
  from typing import 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_tar
label_desc: Use image node_id 4 for calling the TEDLIUM obj's underlying member method code with example usage: obj.__getitem__(n) and returns: self