Speech Emotion Recognition On Ravdess
评估指标
Accuracy
评测结果
各个模型在此基准测试上的表现结果
| Paper Title | Repository | ||
|---|---|---|---|
| VQ-MAE-S-12 (Frame) + Query2Emo | 84.1 | A vector quantized masked autoencoder for speech emotion recognition | |
| CNN-X (Shallow CNN) | 82.99% | Shallow over Deep Neural Networks: A empirical analysis for human emotion classification using audio data | - |
| xlsr-Wav2Vec2.0(FineTuning) | 81.82% | A proposal for Multimodal Emotion Recognition using aural transformers and Action Units on RAVDESS dataset | - |
| CNN-14 (Fine-Tuning) | 76.58% | Multimodal Emotion Recognition on RAVDESS Dataset Using Transfer Learning | - |
| AlexNet (FineTuning) | 61.67% | Multimodal Emotion Recognition on RAVDESS Dataset Using Transfer Learning | - |
0 of 5 row(s) selected.