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 101–125 of 194 papers

TitleStatusHype
Semi-supervsied Learning-based Sound Event Detection using Freuqency Dynamic Convolution with Large Kernel Attention for DCASE Challenge 2023 Task 4—0
Divided spectro-temporal attention for sound event localization and detection in real scenes for DCASE2023 challenge—0
A Multi-Task Learning Framework for Sound Event Detection using High-level Acoustic Characteristics of Sounds—0
Learning to Detect Novel and Fine-Grained Acoustic Sequences Using Pretrained Audio Representations—0
Adversarial Representation Learning for Robust Privacy Preservation in AudioCode0
Leveraging Audio-Tagging Assisted Sound Event Detection using Weakified Strong Labels and Frequency Dynamic Convolutions—0
HiSSNet: Sound Event Detection and Speaker Identification via Hierarchical Prototypical Networks for Low-Resource Headphones—0
Improving Weakly Supervised Sound Event Detection with Causal Intervention—0
AST-SED: An Effective Sound Event Detection Method Based on Audio Spectrogram Transformer—0
Training sound event detection with soft labels from crowdsourced annotations—0
LOCUS: LOcalization with Channel Uncertainty and Sporadic Energy—0
Multi-dimensional frequency dynamic convolution with confident mean teacher for sound event detection—0
Automatic Sound Event Detection and Classification of Great Ape Calls Using Neural NetworksCode0
Impact of visual assistance for automated audio captioning—0
Lightweight Sound Event Detection Model with RepVGG Architecture—0
On Out-of-Distribution Detection for Audio with Deep Nearest NeighborsCode0
Optimizing Temporal Resolution Of Convolutional Recurrent Neural Networks For Sound Event Detection—0
Impact of temporal resolution on convolutional recurrent networks for audio tagging and sound event detection—0
Multi-encoder attention-based architectures for sound recognition with partial visual assistance—0
Binaural Signal Representations for Joint Sound Event Detection and Acoustic Scene Classification—0
Multitask vocal burst modeling with ResNets and pre-trained paralinguistic Conformers—0
Adaptive Few-Shot Learning Algorithm for Rare Sound Event Detection—0
Selective Pseudo-labeling and Class-wise Discriminative Fusion for Sound Event Detection—0
Nonverbal Sound Detection for Disordered Speech—0
SEED: Sound Event Early Detection via Evidential Uncertainty—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