SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 101–125 of 194 papers

TitleStatusHype
Weakly Labeled Sound Event Detection Using Tri-training and Adversarial Learning—0
A benchmark of state-of-the-art sound event detection systems evaluated on synthetic soundscapes—0
Zero-shot Audio Source Separation through Query-based Learningfrom Weakly-labeled Data—0
A Capsule based Approach for Polyphonic Sound Event Detection—0
A Comparative Study of Western and Chinese Classical Music based on Soundscape Models—0
Active Learning for Sound Event Detection—0
Adaptive Few-Shot Learning Algorithm for Rare Sound Event Detection—0
Affinity Mixup for Weakly Supervised Sound Event Detection—0
Aggregation Strategies for Efficient Annotation of Bioacoustic Sound Events Using Active Learning—0
A Multi-Task Learning Framework for Sound Event Detection using High-level Acoustic Characteristics of Sounds—0
An Experimental Study on Joint Modeling for Sound Event Localization and Detection with Source Distance Estimation—0
A Sequence Matching Network for Polyphonic Sound Event Localization and Detection—0
AST-SED: An Effective Sound Event Detection Method Based on Audio Spectrogram Transformer—0
Audio-Based Epileptic Seizure Detection—0
Audiovisual transfer learning for audio tagging and sound event detection—0
Auditory Neural Response Inspired Sound Event Detection Based on Spectro-temporal Receptive Field—0
Automated Bioacoustic Monitoring for South African Bird Species on Unlabeled Data—0
BAT: Learning to Reason about Spatial Sounds with Large Language Models—0
Binaural Signal Representations for Joint Sound Event Detection and Acoustic Scene Classification—0
Channel Compression: Rethinking Information Redundancy among Channels in CNN Architecture—0
Channel-Spatial-Based Few-Shot Bird Sound Event Detection—0
Compact recurrent neural networks for acoustic event detection on low-energy low-complexity platforms—0
Conditioned Time-Dilated Convolutions for Sound Event Detection—0
Crowdsourcing strong labels for sound event detection—0
DASED: A Multi-Domain Dataset for Sound Event Detection Domain Adaptation—0
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All datasetsDESEDL3DAS21WildDESEDMivia Audio EventsMivia Road Events

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ATST-SEDevent-based F1 score63.4—Unverified
2SE-CRNN-16 with DualKDevent-based F1 score55.6—Unverified
3FDY-CRNNevent-based F1 score54—Unverified
4HTS-ATevent-based F1 score50.7—Unverified
5RCTevent-based F1 score49.62—Unverified
6FiltAug SEDevent-based F1 score49.6—Unverified
7SED-SSep baseline dcase task 4 2020 v2event-based F1 score40.7—Unverified
8Baseline dcase task 4 2020 v2event-based F1 score39—Unverified
9Baselineevent-based F1 score25.8—Unverified
10MAT-SEDPSDS10.59—Unverified
#ModelMetricClaimedVerifiedStatus
1PHC SEDnet n=8Error Rate0.56—Unverified
2Quaternion SEDnetError Rate0.52—Unverified
3PHC SEDnet n=16Error Rate0.51—Unverified
4PHC SEDnet n=4Error Rate0.45—Unverified
5PHC SEDnet n=2Error Rate0.39—Unverified
#ModelMetricClaimedVerifiedStatus
1CRNN (with BEATs + Separation)PSDS1 (-5dB)0.13—Unverified
2CRNN (with BEATs)PSDS1 (-5dB)0.07—Unverified
3CRNN (WildDESED + Curriculrm learning)PSDS1 (-5dB)0.05—Unverified
4CRNN (WildDESED)PSDS1 (-5dB)0.05—Unverified
5CRNNPSDS1 (-5dB)0.02—Unverified
#ModelMetricClaimedVerifiedStatus
1DENetRank-1 Recognition Rate0.98—Unverified
#ModelMetricClaimedVerifiedStatus
1DENetRank-1 Recognition Rate1—Unverified