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

Showing 2650 of 194 papers

TitleStatusHype
Self-supervised Audio Teacher-Student Transformer for Both Clip-level and Frame-level TasksCode1
AD-YOLO: You Look Only Once in Training Multiple Sound Event Localization and DetectionCode1
A dataset for Audio-Visual Sound Event Detection in MoviesCode1
A Hybrid System of Sound Event Detection Transformer and Frame-wise Model for DCASE 2022 Task 4Code1
Sound Event Localization and Detection for Real Spatial Sound Scenes: Event-Independent Network and Data Augmentation ChainsCode1
Few-shot bioacoustic event detection at the DCASE 2022 challengeCode1
Frequency Dependent Sound Event Detection for DCASE 2022 Challenge Task 4Code1
Frequency Dynamic Convolution: Frequency-Adaptive Pattern Recognition for Sound Event DetectionCode1
Threshold Independent Evaluation of Sound Event Detection ScoresCode1
Zero-shot Audio Source Separation through Query-based Learning from Weakly-labeled DataCode1
RCT: Random Consistency Training for Semi-supervised Sound Event DetectionCode1
Couple Learning for semi-supervised sound event detectionCode1
PHNNs: Lightweight Neural Networks via Parameterized Hypercomplex ConvolutionsCode1
FilterAugment: An Acoustic Environmental Data Augmentation MethodCode1
Sound Event Detection Transformer: An Event-based End-to-End Model for Sound Event DetectionCode1
SALSA: Spatial Cue-Augmented Log-Spectrogram Features for Polyphonic Sound Event Localization and DetectionCode1
The impact of non-target events in synthetic soundscapes for sound event detectionCode1
You Only Hear Once: A YOLO-like Algorithm for Audio Segmentation and Sound Event DetectionCode1
What Makes Sound Event Localization and Detection Difficult? Insights from Error AnalysisCode1
Weakly-Supervised Classification and Detection of Bird Sounds in the Wild.Code1
Heavily Augmented Sound Event Detection utilizing Weak PredictionsCode1
DCASE 2021 Task 3: Spectrotemporally-aligned Features for Polyphonic Sound Event Localization and DetectionCode1
Improving weakly supervised sound event detection with self-supervised auxiliary tasksCode1
Forward-Backward Convolutional Recurrent Neural Networks and Tag-Conditioned Convolutional Neural Networks for Weakly Labeled Semi-supervised Sound Event DetectionCode1
DENet: a deep architecture for audio surveillance applicationsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ATST-SEDevent-based F1 score63.4Unverified
2SE-CRNN-16 with DualKDevent-based F1 score55.6Unverified
3FDY-CRNNevent-based F1 score54Unverified
4HTS-ATevent-based F1 score50.7Unverified
5RCTevent-based F1 score49.62Unverified
6FiltAug SEDevent-based F1 score49.6Unverified
7SED-SSep baseline dcase task 4 2020 v2event-based F1 score40.7Unverified
8Baseline dcase task 4 2020 v2event-based F1 score39Unverified
9Baselineevent-based F1 score25.8Unverified
10MAT-SEDPSDS10.59Unverified
#ModelMetricClaimedVerifiedStatus
1PHC SEDnet n=8Error Rate0.56Unverified
2Quaternion SEDnetError Rate0.52Unverified
3PHC SEDnet n=16Error Rate0.51Unverified
4PHC SEDnet n=4Error Rate0.45Unverified
5PHC SEDnet n=2Error Rate0.39Unverified
#ModelMetricClaimedVerifiedStatus
1CRNN (with BEATs + Separation)PSDS1 (-5dB)0.13Unverified
2CRNN (with BEATs)PSDS1 (-5dB)0.07Unverified
3CRNN (WildDESED + Curriculrm learning)PSDS1 (-5dB)0.05Unverified
4CRNN (WildDESED)PSDS1 (-5dB)0.05Unverified
5CRNNPSDS1 (-5dB)0.02Unverified
#ModelMetricClaimedVerifiedStatus
1DENetRank-1 Recognition Rate0.98Unverified
#ModelMetricClaimedVerifiedStatus
1DENetRank-1 Recognition Rate1Unverified