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Sound Event Detection On Desed

Metrics

event-based F1 score

Results

Performance results of various models on this benchmark

Model Name	event-based F1 score	Paper Title	Repository
HTS-AT	50.7	HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection	-
ABC + MDFD-CRNN	-	Pushing the Limit of Sound Event Detection with Multi-Dilated Frequency Dynamic Convolution
RCT	49.62	RCT: Random Consistency Training for Semi-supervised Sound Event Detection
MAT-SED	-	MAT-SED: A Masked Audio Transformer with Masked-Reconstruction Based Pre-training for Sound Event Detection
Baseline	25.8	Sound event detection in domestic environments withweakly labeled data and soundscape synthesis
ATST-SED	63.4	Fine-tune the pretrained ATST model for sound event detection
FDY-CRNN	54.0	Frequency Dynamic Convolution: Frequency-Adaptive Pattern Recognition for Sound Event Detection	-
SE-CRNN-16 with DualKD	55.6	Dual Knowledge Distillation for Efficient Sound Event Detection	-
SED-SSep baseline dcase task 4 2020 v2	40.7	Improving Sound Event Detection In Domestic Environments Using Sound Separation
MDFD-CRNN	-	Pushing the Limit of Sound Event Detection with Multi-Dilated Frequency Dynamic Convolution
Baseline dcase task 4 2020 v2	39.0	Training Sound Event Detection On A Heterogeneous Dataset
FiltAug SED	49.6	Heavily Augmented Sound Event Detection utilizing Weak Predictions
JiTTER	-	JiTTER: Jigsaw Temporal Transformer for Event Reconstruction for Self-Supervised Sound Event Detection

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