Ryerson Audio-Visual Database of Emotional Speech and Song
The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) contains 7,356 files (total size: 24.8 GB). The database contains 24 professional actors (12 female, 12 male), vocalizing two lexically-matched statements in a neutral North American accent. Speech includes calm, happy, sad, angry, fearful, surprise, and disgust expressions, and song contains calm, happy, sad, angry, and fearful emotions. Each expression is produced at two levels of emotional intensity (normal, strong), with an additional neutral expression. All conditions are available in three modality formats: Audio-only (16bit, 48kHz .wav), Audio-Video (720p H.264, AAC 48kHz, .mp4), and Video-only (no sound). Note, there are no song files for Actor_18.
Paper: The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American English
Source:
Variants: RAVDESS
This dataset is used in 5 benchmarks:
| Task | Model | Paper | Date |
|---|---|---|---|
| Emotion Recognition | MultiMAE-DER | MultiMAE-DER: Multimodal Masked Autoencoder for … | 2024-04-28 |
| Audio Classification | ASM-RH-A | Mixer is more than just … | 2024-02-28 |
| Speech Emotion Recognition | VQ-MAE-S-12 (Frame) + Query2Emo | A vector quantized masked autoencoder … | 2023-04-21 |
| Emotion Recognition | Intermediate-Attention-Fusion | Self-attention fusion for audiovisual emotion … | 2022-01-26 |
Recent papers with results on this dataset: