Sound Event Detection

Sound Event Detection (SED) is the task of recognizing the sound events and their respective temporal start and end time in a recording. Sound events in real life do not always occur in isolation, but tend to considerably overlap with each other. Recognizing such overlapping sound events is referred as polyphonic SED.

Source: A report on sound event detection with different binaural features

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 161–170 of 194 papers

Title	Date	Tasks	Status
Multi-encoder attention-based architectures for sound recognition with partial visual assistance	Sep 26, 2022	Audio TaggingEvent Detection	—Unverified
Multitask frame-level learning for few-shot sound event detection	Mar 17, 2024	Data AugmentationEvent Detection	—Unverified
Multitask vocal burst modeling with ResNets and pre-trained paralinguistic Conformers	Jun 24, 2022	Emotion RecognitionEvent Detection	—Unverified
Nonverbal Sound Detection for Disordered Speech	Feb 15, 2022	Event DetectionSound Event Detection	—Unverified
Online Active Learning For Sound Event Detection	Sep 25, 2023	Active LearningEvent Detection	—Unverified
Optimizing Temporal Resolution Of Convolutional Recurrent Neural Networks For Sound Event Detection	Oct 18, 2022	Event DetectionSound Event Detection	—Unverified
Peer Collaborative Learning for Polyphonic Sound Event Detection	Oct 7, 2021	Event DetectionKnowledge Distillation	—Unverified
Power pooling: An adaptive pooling function for weakly labelled sound event detection	Oct 20, 2020	Event DetectionMultiple Instance Learning	—Unverified
Proposal-based Few-shot Sound Event Detection for Speech and Environmental Sounds with Perceivers	Jul 28, 2021	Event DetectionKeyword Spotting	—Unverified
Pseudo Strong Labels from Frame-Level Predictions for Weakly Supervised Sound Event Detection	Jan 7, 2025	Event DetectionSound Event Detection	—Unverified

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All datasets DESED L3DAS21 WildDESED Mivia Audio Events Mivia Road Events

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ATST-SED	event-based F1 score	63.4	—	Unverified
2	SE-CRNN-16 with DualKD	event-based F1 score	55.6	—	Unverified
3	FDY-CRNN	event-based F1 score	54	—	Unverified
4	HTS-AT	event-based F1 score	50.7	—	Unverified
5	RCT	event-based F1 score	49.62	—	Unverified
6	FiltAug SED	event-based F1 score	49.6	—	Unverified
7	SED-SSep baseline dcase task 4 2020 v2	event-based F1 score	40.7	—	Unverified
8	Baseline dcase task 4 2020 v2	event-based F1 score	39	—	Unverified
9	Baseline	event-based F1 score	25.8	—	Unverified
10	MAT-SED	PSDS1	0.59	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PHC SEDnet n=8	Error Rate	0.56	—	Unverified
2	Quaternion SEDnet	Error Rate	0.52	—	Unverified
3	PHC SEDnet n=16	Error Rate	0.51	—	Unverified
4	PHC SEDnet n=4	Error Rate	0.45	—	Unverified
5	PHC SEDnet n=2	Error Rate	0.39	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CRNN (with BEATs + Separation)	PSDS1 (-5dB)	0.13	—	Unverified
2	CRNN (with BEATs)	PSDS1 (-5dB)	0.07	—	Unverified
3	CRNN (WildDESED + Curriculrm learning)	PSDS1 (-5dB)	0.05	—	Unverified
4	CRNN (WildDESED)	PSDS1 (-5dB)	0.05	—	Unverified
5	CRNN	PSDS1 (-5dB)	0.02	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DENet	Rank-1 Recognition Rate	0.98	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DENet	Rank-1 Recognition Rate	1	—	Unverified