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 11–20 of 194 papers

Title	Date	Tasks	Status	Hype
ACCDOA: Activity-Coupled Cartesian Direction of Arrival Representation for Sound Event Localization and Detection	Oct 29, 2020	Event DetectionSound Event Detection	CodeCode Available	1
FilterAugment: An Acoustic Environmental Data Augmentation Method	Oct 7, 2021	Data AugmentationEvent Detection	CodeCode Available	1
A Hybrid System of Sound Event Detection Transformer and Frame-wise Model for DCASE 2022 Task 4	Oct 18, 2022	Event DetectionMetric Learning	CodeCode Available	1
Forward-Backward Convolutional Recurrent Neural Networks and Tag-Conditioned Convolutional Neural Networks for Weakly Labeled Semi-supervised Sound Event Detection	Mar 11, 2021	Event DetectionSound Event Detection	CodeCode Available	1
Few-shot bioacoustic event detection at the DCASE 2022 challenge	Jul 14, 2022	Event DetectionSound Event Detection	CodeCode Available	1
DENet: a deep architecture for audio surveillance applications	Jan 11, 2021	DenoisingSound Event Detection	CodeCode Available	1
A dataset for Audio-Visual Sound Event Detection in Movies	Feb 14, 2023	Event DetectionSelf-Driving Cars	CodeCode Available	1
Diversifying and Expanding Frequency-Adaptive Convolution Kernels for Sound Event Detection	Jun 8, 2024	Event DetectionSound Event Detection	CodeCode Available	1
Exploring Performance-Complexity Trade-Offs in Sound Event Detection Models	Mar 14, 2025	Audio TaggingEvent Detection	CodeCode Available	1
DCASE 2021 Task 3: Spectrotemporally-aligned Features for Polyphonic Sound Event Localization and Detection	Jun 29, 2021	Audio ClassificationDirection of Arrival Estimation	CodeCode Available	1

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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