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Audio Tagging On Audioset

Metrics

mean average precision

Results

Performance results of various models on this benchmark

Model Name	mean average precision	Paper Title	Repository
PSLA	0.474	PSLA: Improving Audio Tagging with Pretraining, Sampling, Labeling, and Aggregation
Audio Spectrogram Transformer	0.485	AST: Audio Spectrogram Transformer
DyMN-L (Audio-Only, Single)	0.490	Dynamic Convolutional Neural Networks as Efficient Pre-trained Audio Models
PaSST	0.496	Efficient Training of Audio Transformers with Patchout
mn40_as (Single)	0.483	Efficient Large-scale Audio Tagging via Transformer-to-CNN Knowledge Distillation
CAV-MAE (Audio-Visual)	0.512	Contrastive Audio-Visual Masked Autoencoder
CNN14	0.431	PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition
ERANN-1-6	0.450	ERANNs: Efficient Residual Audio Neural Networks for Audio Pattern Recognition	-
mn40_as (Ensemble)	0.498	Efficient Large-scale Audio Tagging via Transformer-to-CNN Knowledge Distillation
CAV-MAE (Audio-Only)	0.466	Contrastive Audio-Visual Masked Autoencoder
ST-SED	0.467	Zero-shot Audio Source Separation through Query-based Learning from Weakly-labeled Data

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