AST: Audio Spectrogram Transformer

Benchmark Model Rank Results
audio-classification-on-audiosetAST (Ensemble)#17Test mAP: 0.485
audio-classification-on-audiosetAST (Single)#31Test mAP: 0.459
audio-classification-on-esc-50AST-P#13Top-1 Accuracy: 95.6PRE-TRAINING DATASET: AudioSet, ImageNet
audio-classification-on-esc-50AST-S#21Top-1 Accuracy: 88.7PRE-TRAINING DATASET: ImageNet
audio-classification-on-speech-commands-1AST-S#2Accuracy: 98.11±0.05
audio-tagging-on-audiosetAudio Spectrogram Transformer#9mean average precision: 0.485
keyword-spotting-on-google-speech-commandsAudio Spectrogram Transformer#26Google Speech Commands V2 35: 98.11
speech-emotion-recognition-on-crema-dViT#4Accuracy: 67.81
time-series-on-speech-commandsViT#2% Test Accuracy: 98.11