class_docstr: VCTK speech synthesis dataset.
  
  The dataset is broken into two separate configs, each containing audio
  recorded using different microphones.  They are split this way for consistency
  with previous releases which only included a single microphone.
class_docstr_tok: ["VCTK","speech","synthesis","dataset",".","The","dataset","is","broken","into","two","separate","configs",",","each","containing","audio","recorded","using","different","microphones",".","They","are","split","this","way","for","consistency","with","previous","releases","which","only","included","a","single","microphone","."]
code: def _split_generators(self, dl_manager):
      extracted_dir = dl_manager.download_and_extract(_DL_URL)
      self._populate_metadata(extracted_dir)
      return [
          tfds.core.SplitGenerator(
              name=tfds.Split.TRAIN,
              gen_kwargs={"extracted_dir": extracted_dir},
          ),
      ]
  
file_path: datasets/tensorflow_datasets/audio/vctk.py
imports: import os
  from absl import logging
  import numpy
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 2 for calling the Vctk obj's underlying member method code with example usage: obj._split_generators(dl_manager) and returns: list