class_docstr: *LJSpeech-1.1* :cite:`ljspeech17` dataset.
  
  Args:
      root (str or Path): Path to the directory where the dataset is found or downloaded.
      url (str, optional): The URL to download the dataset from.
          (default: ``"https://data.keithito.com/data/speech/LJSpeech-1.1.tar.bz2"``)
      folder_in_archive (str, optional):
          The top-level directory of the dataset. (default: ``"wavs"``)
      download (bool, optional):
          Whether to download the dataset if it is not found at root path. (default: ``False``).
class_docstr_tok: ["*","LJSpeech-1.1","*",":","cite",":","`","ljspeech17","`","dataset",".","Args",":","root","(","str","or","Path",")",":","Path","to","the","directory","where","the","dataset","is","found","or","downloaded",".","url","(","str",",","optional",")",":","The","URL","to","download","the","dataset","from",".","(","default",":","``","``","https",":","\/\/data.keithito.com\/data\/speech\/LJSpeech-1.1.tar.bz2","''","``",")","folder_in_archive","(","str",",","optional",")",":","The","top-level","directory","of","the","dataset",".","(","default",":","``","``","wavs","''","``",")","download","(","bool",",","optional",")",":","Whether","to","download","the","dataset","if","it","is","not","found","at","root","path",".","(","default",":","``","False","``",")","."]
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
      str:
          Normalized Transcript
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","str",":","Normalized","Transcript"]
code: def __getitem__(self, n: int) -> Tuple[Tensor, int, str, str]:
      """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
          str:
              Normalized Transcript
      """
      line = self._flist[n]
      fileid, transcript, normalized_transcript = line
      fileid_audio = self._path / (fileid + ".wav")
  
      # Load audio
      waveform, sample_rate = torchaudio.load(fileid_audio)
  
      return (
          waveform,
          sample_rate,
          transcript,
          normalized_transcript,
      )
  
file_path: audio/src/torchaudio/datasets/ljspeech.py
imports: import csv
  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 3 for calling the LJSPEECH obj's underlying member method code with example usage: obj.__getitem__(n) and returns: waveform,  sample_rate,  transcript,  normalized_transcript