class_docstr: The audio part of CREMA-D dataset for emotion recognition.
class_docstr_tok: ["The","audio","part","of","CREMA-D","dataset","for","emotion","recognition","."]
code: def _info(self):
      return tfds.core.DatasetInfo(
          builder=self,
          description=_DESCRIPTION,
          features=tfds.features.FeaturesDict(
              {
                  "audio": tfds.features.Audio(
                      file_format="wav", sample_rate=16000
                  ),
                  "label": tfds.features.ClassLabel(names=list(LABELS)),
                  "speaker_id": np.str_,
              }
          ),
          supervised_keys=("audio", "label"),
          homepage=_HOMEPAGE,
          citation=_CITATION,
      )
  
file_path: datasets/tensorflow_datasets/audio/crema_d.py
imports: from __future__ import annotations
  import collections
  import os
  import numpy
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 1 for calling the CremaD obj's underlying member method code with example usage: obj._info() and returns: tfds