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: Loads a TEDLIUM dataset sample given a file name and corresponding sentence name.
  
  Args:
      fileid (str): File id to identify both text and audio files corresponding to the sample
      line (int): Line identifier for the sample inside the text file
      path (str): Dataset root path
  
  Returns:
      (Tensor, int, str, int, int, int):
      ``(waveform, sample_rate, transcript, talk_id, speaker_id, identifier)``
docstr_tok: ["Loads","a","TEDLIUM","dataset","sample","given","a","file","name","and","corresponding","sentence","name",".","Args",":","fileid","(","str",")",":","File","id","to","identify","both","text","and","audio","files","corresponding","to","the","sample","line","(","int",")",":","Line","identifier","for","the","sample","inside","the","text","file","path","(","str",")",":","Dataset","root","path","Returns",":","(","Tensor",",","int",",","str",",","int",",","int",",","int",")",":","``","(","waveform",",","sample_rate",",","transcript",",","talk_id",",","speaker_id",",","identifier",")","``"]
code: def _load_tedlium_item(
      self, fileid: str, line: int, path: str
  ) -> Tuple[Tensor, int, str, int, int, int]:
      """Loads a TEDLIUM dataset sample given a file name and corresponding sentence name.
  
      Args:
          fileid (str): File id to identify both text and audio files corresponding to the sample
          line (int): Line identifier for the sample inside the text file
          path (str): Dataset root path
  
      Returns:
          (Tensor, int, str, int, int, int):
          ``(waveform, sample_rate, transcript, talk_id, speaker_id, identifier)``
      """
      transcript_path = os.path.join(path, "stm", fileid)
      with open(transcript_path + ".stm") as f:
          transcript = f.readlines()[line]
          (
              talk_id,
              _,
              speaker_id,
              start_time,
              end_time,
              identifier,
              transcript,
          ) = transcript.split(" ", 6)
  
      wave_path = os.path.join(path, "sph", fileid)
      waveform, sample_rate = self._load_audio(
          wave_path + self._ext_audio,
          start_time=start_time,
          end_time=end_time,
      )
  
      return (
          waveform,
          sample_rate,
          transcript,
          talk_id,
          speaker_id,
          identifier,
      )
  
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 2 for calling the TEDLIUM obj's underlying member method code with example usage: obj._load_tedlium_item(fileid, line, path) and returns: waveform,  sample_rate,  transcript,  talk_id,  speaker_id,  identifier