CREMA-D

Viewer-compatible mirror of the audio portion of CREMA-D (Crowd-sourced Emotional Multimodal Actors Dataset).

This repository republishes the audio files from myleslinder/crema-d as Hub-native Parquet shards so the Hugging Face viewer, search, and filtering work without a custom loading script.

What is included

• 7,442 WAV clips
• 91 actors
• 12 fixed sentence prompts
• 6 emotion labels: anger, disgust, fear, happy, neutral, sad
• 4 intensity codes: LO, MD, HI, XX

Columns

• audio: WAV audio at 16000 Hz
• actor_id: actor identifier, for example 1001
• sentence_code: short utterance code, for example DFA
• sentence: decoded utterance text
• emotion_code: short emotion code, for example ANG
• emotion_intensity: decoded intensity label
• intensity_code: original intensity code
• label: class label for the emotion
• source_file: original filename

Notes

• This is an audio-only mirror of the Hugging Face dataset myleslinder/crema-d.
• The original CREMA-D project also includes video assets, but those files are not part of myleslinder/crema-d.
• The original script-based dataset disabled the Hub viewer because it relied on arbitrary Python code. This mirror uses Parquet files instead.

Source

• Original Hugging Face dataset: myleslinder/crema-d
• Original project: https://github.com/CheyneyComputerScience/CREMA-D

Citation

@article{cao2014crema,
  title={CREMA-D: Crowd-sourced Emotional Multimodal Actors Dataset},
  author={Cao, H. and Cooper, D. G. and Keutmann, M. K. and Gur, R. C. and Nenkova, A. and Verma, R.},
  journal={IEEE Transactions on Affective Computing},
  volume={5},
  number={4},
  pages={377--390},
  year={2014},
  doi={10.1109/TAFFC.2014.2336244}
}