Audio Tagging On Audioset
Métriques
mean average precision
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | mean average precision |
|---|---|
| psla-improving-audio-event-classification | 0.474 |
| ast-audio-spectrogram-transformer | 0.485 |
| dynamic-convolutional-neural-networks-as | 0.490 |
| efficient-training-of-audio-transformers-with | 0.496 |
| efficient-large-scale-audio-tagging-via | 0.483 |
| contrastive-audio-visual-masked-autoencoder | 0.512 |
| panns-large-scale-pretrained-audio-neural-1 | 0.431 |
| eranns-efficient-residual-audio-neural | 0.450 |
| efficient-large-scale-audio-tagging-via | 0.498 |
| contrastive-audio-visual-masked-autoencoder | 0.466 |
| zero-shot-audio-source-separation-through | 0.467 |