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 171–180 of 194 papers

Title	Date	Tasks	Status
Regularized Contrastive Pre-training for Few-shot Bioacoustic Sound Detection	Sep 16, 2023	Event DetectionFew-Shot Learning	CodeCode Available
Memory Controlled Sequential Self Attention for Sound Recognition	May 13, 2020	Event DetectionSound Event Detection	CodeCode Available
Adversarial Representation Learning for Robust Privacy Preservation in Audio	Apr 29, 2023	Event DetectionRepresentation Learning	CodeCode Available
Guided Learning Convolution System for DCASE 2019 Task 4	Sep 11, 2019	Event DetectionSound Event Detection	CodeCode Available
Robust sound event detection in bioacoustic sensor networks	May 20, 2019	Data AugmentationEvent Detection	CodeCode Available
Leveraging Geometrical Acoustic Simulations of Spatial Room Impulse Responses for Improved Sound Event Detection and Localization	Sep 6, 2023	Event DetectionSound Event Detection	CodeCode Available
Evaluation of post-processing algorithms for polyphonic sound event detection	Jun 17, 2019	Audio TaggingEvent Detection	CodeCode Available
Unsupervised Audio-Caption Aligning Learns Correspondences between Individual Sound Events and Textual Phrases	Oct 6, 2021	Event DetectionRetrieval	CodeCode Available
Learning Sound Events From Webly Labeled Data	Nov 25, 2018	Event DetectionSound Event Detection	CodeCode Available
Adaptive pooling operators for weakly labeled sound event detection	Apr 26, 2018	Event DetectionMultiple Instance Learning	CodeCode Available

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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