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
Affinity Mixup for Weakly Supervised Sound Event Detection	Jun 21, 2021	Event DetectionSound Event Detection	—Unverified
SoundDet: Polyphonic Moving Sound Event Detection and Localization from Raw Waveform	Jun 13, 2021	Event DetectionSound Event Detection	—Unverified
Audiovisual transfer learning for audio tagging and sound event detection	Jun 9, 2021	Audio TaggingEvent Detection	—Unverified
Cross-Referencing Self-Training Network for Sound Event Detection in Audio Mixtures	May 27, 2021	Audio TaggingEvent Detection	CodeCode Available
USM-SED - A Dataset for Polyphonic Sound Event Detection in Urban Sound Monitoring Scenarios	May 6, 2021	Dataset GenerationEvent Detection	—Unverified
DESED-FL and URBAN-FL: Federated Learning Datasets for Sound Event Detection	Feb 17, 2021	Event DetectionFederated Learning	—Unverified
Deep Convolutional and Recurrent Networks for Polyphonic Instrument Classification from Monophonic Raw Audio Waveforms	Feb 13, 2021	Audio ClassificationClassification	—Unverified
Sound Event Detection in Urban Audio With Single and Multi-Rate PCEN	Feb 6, 2021	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
Soft-Median Choice: An Automatic Feature Smoothing Method for Sound Event Detection	Nov 25, 2020	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