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 91–100 of 194 papers

Title	Date	Tasks	Status
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
Do sound event representations generalize to other audio tasks? A case study in audio transfer learning	Jun 21, 2021	Event DetectionSound Event Detection	—Unverified
Dual Knowledge Distillation for Efficient Sound Event Detection	Feb 5, 2024	Event DetectionKnowledge Distillation	—Unverified
Effect of noise suppression losses on speech distortion and ASR performance	Nov 23, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
End-to-End Polyphonic Sound Event Detection Using Convolutional Recurrent Neural Networks with Learned Time-Frequency Representation Input	May 9, 2018	Event DetectionSound Event Detection	—Unverified
Energy Consumption Trends in Sound Event Detection Systems	Sep 13, 2024	Event DetectionSound Event Detection	—Unverified
Evaluating Classification Systems Against Soft Labels with Fuzzy Precision and Recall	Sep 25, 2023	Event DetectionSound Event Detection	—Unverified
Exploring the Potential of SSL Models for Sound Event Detection	May 17, 2025	Event DetectionModel Selection	—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