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

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Showing 141–150 of 194 papers

Title	Date	Tasks	Status
Sound Event Detection in Multichannel Audio using Convolutional Time-Frequency-Channel Squeeze and Excitation	Aug 4, 2019	Event DetectionSound Event Detection	—Unverified
Sound Event Detection in Synthetic Audio: Analysis of the DCASE 2016 Task Results	Nov 15, 2017	Event DetectionGeneral Classification	—Unverified
Sound Event Detection in Urban Audio With Single and Multi-Rate PCEN	Feb 6, 2021	Event DetectionSound Event Detection	—Unverified
Sound event detection via dilated convolutional recurrent neural networks	Jul 20, 2020	Event DetectionSound Event Detection	—Unverified
Sound Event Detection with Binary Neural Networks on Tightly Power-Constrained IoT Devices	Jan 12, 2021	Event DetectionObject Recognition	—Unverified
SwG-former: A Sliding-Window Graph Convolutional Network for Simultaneous Spatial-Temporal Information Extraction in Sound Event Localization and Detection	Oct 21, 2023	Event DetectionSound Event Detection	—Unverified
Synthetic data enables context-aware bioacoustic sound event detection	Mar 1, 2025	Event DetectionIn-Context Learning	—Unverified
The NIGENS General Sound Events Database	Feb 21, 2019	Event DetectionSound Event Detection	—Unverified
tinyCLAP: Distilling Constrastive Language-Audio Pretrained Models	Nov 24, 2023	Audio GenerationEvent Detection	—Unverified
Towards Understanding of Frequency Dependence on Sound Event Detection	Feb 11, 2025	Data AugmentationEvent 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