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 161–170 of 194 papers

Title	Date	Tasks	Status	Hype
Sound Event Detection with Depthwise Separable and Dilated Convolutions	Feb 2, 2020	Event DetectionSound Event Detection	CodeCode Available	1
Compact recurrent neural networks for acoustic event detection on low-energy low-complexity platforms	Jan 29, 2020	Event DetectionQuantization	—Unverified	0
Sound event detection in domestic environments withweakly labeled data and soundscape synthesis	Oct 26, 2019	Event DetectionSound Event Detection	CodeCode Available	0
Musical Instrument Playing Technique Detection Based on FCN: Using Chinese Bowed-Stringed Instrument as an Example	Oct 20, 2019	Event DetectionInstrument Playing Technique Detection	CodeCode Available	0
Weakly Labeled Sound Event Detection Using Tri-training and Adversarial Learning	Oct 14, 2019	Event DetectionSound Event Detection	—Unverified	0
Guided Learning Convolution System for DCASE 2019 Task 4	Sep 11, 2019	Event DetectionSound Event Detection	CodeCode Available	0
Audio-Based Epileptic Seizure Detection	Sep 6, 2019	Event DetectionSeizure Detection	—Unverified	0
Sound Event Detection in Multichannel Audio using Convolutional Time-Frequency-Channel Squeeze and Excitation	Aug 4, 2019	Event DetectionSound Event Detection	—Unverified	0
City classification from multiple real-world sound scenes	Jul 29, 2019	Acoustic Scene ClassificationClassification	CodeCode Available	0
Language Modelling for Sound Event Detection with Teacher Forcing and Scheduled Sampling	Jul 19, 2019	Event DetectionLanguage Modelling	CodeCode Available	0

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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