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Instrument Recognition On Openmic 2018
Metrics
mean average precision
Results
Performance results of various models on this benchmark
| Paper Title | Repository | ||
|---|---|---|---|
| DyMN-L | 0.855 | Dynamic Convolutional Neural Networks as Efficient Pre-trained Audio Models | |
| EAsT-KD + PaSST | .852 | Audio Embeddings as Teachers for Music Classification | |
| EAsT-Final + PaSST | .847 | Audio Embeddings as Teachers for Music Classification | |
| PaSST | 0.843 | Efficient Training of Audio Transformers with Patchout |
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