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 121–130 of 194 papers

Title	Date	Tasks	Status
Channel-Spatial-Based Few-Shot Bird Sound Event Detection	Jun 18, 2023	Event DetectionFew-Shot Learning	—Unverified
Compact recurrent neural networks for acoustic event detection on low-energy low-complexity platforms	Jan 29, 2020	Event DetectionQuantization	—Unverified
Conditioned Time-Dilated Convolutions for Sound Event Detection	Jul 10, 2020	Event DetectionLanguage Modelling	—Unverified
Crowdsourcing strong labels for sound event detection	Jul 26, 2021	Event DetectionSound Event Detection	—Unverified
DASED: A Multi-Domain Dataset for Sound Event Detection Domain Adaptation	Oct 19, 2018	Domain AdaptationEvent Detection	—Unverified
DCASE 2024 Task 4: Sound Event Detection with Heterogeneous Data and Missing Labels	Jun 12, 2024	Event DetectionMissing Labels	—Unverified
Deep Convolutional and Recurrent Networks for Polyphonic Instrument Classification from Monophonic Raw Audio Waveforms	Feb 13, 2021	Audio ClassificationClassification	—Unverified
DESED-FL and URBAN-FL: Federated Learning Datasets for Sound Event Detection	Feb 17, 2021	Event DetectionFederated Learning	—Unverified
DiffSED: Sound Event Detection with Denoising Diffusion	Aug 14, 2023	DecoderDenoising	—Unverified
Divided spectro-temporal attention for sound event localization and detection in real scenes for DCASE2023 challenge	Jun 5, 2023	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