Help protect the Great Barrier Reef with TensorFlow on Kaggle Join Challenge


  • Description:

CREMA-D is an audio-visual data set for emotion recognition. The data set consists of facial and vocal emotional expressions in sentences spoken in a range of basic emotional states (happy, sad, anger, fear, disgust, and neutral). 7,442 clips of 91 actors with diverse ethnic backgrounds were collected. This release contains only the audio stream from the original audio-visual recording. The samples are splitted between train, validation and testing so that samples from each speaker belongs to exactly one split.

Split Examples
'test' 1,556
'train' 5,144
'validation' 738
  • Features:
    'audio': Audio(shape=(None,), dtype=tf.int64),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=6),
    'speaker_id': tf.string,
  • Citation:
  title={ {CREMA-D}: Crowd-sourced emotional multimodal actors dataset},
  author={Cao, Houwei and Cooper, David G and Keutmann, Michael K and Gur, Ruben C and Nenkova, Ani and Verma, Ragini},
  journal={IEEE transactions on affective computing},