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

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Showing 151–175 of 194 papers

TitleStatusHype
Sound Event Detection in Domestic Environments using Dense Recurrent Neural Network—0
Improving Sound Event Detection Metrics: Insights from DCASE 2020—0
Power pooling: An adaptive pooling function for weakly labelled sound event detection—0
Sound event detection via dilated convolutional recurrent neural networks—0
Conditioned Time-Dilated Convolutions for Sound Event Detection—0
Channel Compression: Rethinking Information Redundancy among Channels in CNN Architecture—0
Memory Controlled Sequential Self Attention for Sound RecognitionCode0
Incremental Learning Algorithm for Sound Event Detection—0
Multi-Branch Learning for Weakly-Labeled Sound Event Detection—0
A Comparative Study of Western and Chinese Classical Music based on Soundscape Models—0
A Sequence Matching Network for Polyphonic Sound Event Localization and Detection—0
Active Learning for Sound Event Detection—0
Compact recurrent neural networks for acoustic event detection on low-energy low-complexity platforms—0
Sound event detection in domestic environments withweakly labeled data and soundscape synthesisCode0
Musical Instrument Playing Technique Detection Based on FCN: Using Chinese Bowed-Stringed Instrument as an ExampleCode0
Weakly Labeled Sound Event Detection Using Tri-training and Adversarial Learning—0
Guided Learning Convolution System for DCASE 2019 Task 4Code0
Audio-Based Epileptic Seizure Detection—0
Sound Event Detection in Multichannel Audio using Convolutional Time-Frequency-Channel Squeeze and Excitation—0
City classification from multiple real-world sound scenesCode0
Language Modelling for Sound Event Detection with Teacher Forcing and Scheduled SamplingCode0
Evaluation of post-processing algorithms for polyphonic sound event detectionCode0
Guided learning for weakly-labeled semi-supervised sound event detectionCode0
Specialized Decision Surface and Disentangled Feature for Weakly-Supervised Polyphonic Sound Event DetectionCode0
Robust sound event detection in bioacoustic sensor networksCode0
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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