Perceiver-based Emotion Recognition

This model is a Perceiver-based (https://huggingface.co/docs/transformers/model_doc/perceiver) emotion recognition model trained on RAVDESS dataset (https://zenodo.org/record/1188976#.Y5iqPy2B1QI). The model is trained using 3 modalities: video, audio, and text.

For details on the data collection, check here: https://zenodo.org/record/1188976

The feature extraction for each modality and training procedure follows the steps mentioned here: https://dl.acm.org/doi/10.1145/3551876.3554806

Intended uses

You can use the raw model for directly recognize emotion (classes: 01 = neutral, 02 = calm, 03 = happy, 04 = sad, 05 = angry, 06 = fearful, 07 = disgust, 08 = surprised) or fine-tune on a downstream task.

Limitations

The model is trained on only one dataset and uses 8 specific classes of emotions. The limitation lies in the lack of diversity in the demographics and emotions.

Downloads last month
50
Inference Providers NEW
This model is not currently available via any of the supported third-party Inference Providers, and the model is not deployed on the HF Inference API.

Space using tahiyacy/emotion-recognition 1