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 51–100 of 194 papers

TitleStatusHype
Interactive Dual-Conformer with Scene-Inspired Mask for Soft Sound Event Detection—0
AudioLog: LLMs-Powered Long Audio Logging with Hybrid Token-Semantic Contrastive LearningCode0
SwG-former: A Sliding-Window Graph Convolutional Network for Simultaneous Spatial-Temporal Information Extraction in Sound Event Localization and Detection—0
Performance and energy balance: a comprehensive study of state-of-the-art sound event detection systemsCode0
Online Active Learning For Sound Event Detection—0
Evaluating Classification Systems Against Soft Labels with Fuzzy Precision and Recall—0
Regularized Contrastive Pre-training for Few-shot Bioacoustic Sound DetectionCode0
Semi-supervised Sound Event Detection with Local and Global Consistency Regularization—0
Fine-tune the pretrained ATST model for sound event detectionCode1
Leveraging Geometrical Acoustic Simulations of Spatial Room Impulse Responses for Improved Sound Event Detection and LocalizationCode0
Pretraining Representations for Bioacoustic Few-shot Detection using Supervised Contrastive LearningCode1
Leveraging Language Model Capabilities for Sound Event Detection—0
DiffSED: Sound Event Detection with Denoising Diffusion—0
Post-Processing Independent Evaluation of Sound Event Detection SystemsCode1
Auditory Neural Response Inspired Sound Event Detection Based on Spectro-temporal Receptive Field—0
Channel-Spatial-Based Few-Shot Bird Sound Event Detection—0
Few-shot bioacoustic event detection at the DCASE 2023 challengeCode1
Semi-supervsied Learning-based Sound Event Detection using Freuqency Dynamic Convolution with Large Kernel Attention for DCASE Challenge 2023 Task 4—0
Self-supervised Audio Teacher-Student Transformer for Both Clip-level and Frame-level TasksCode1
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
WavCaps: A ChatGPT-Assisted Weakly-Labelled Audio Captioning Dataset for Audio-Language Multimodal ResearchCode2
AD-YOLO: You Look Only Once in Training Multiple Sound Event Localization and DetectionCode1
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
A dataset for Audio-Visual Sound Event Detection in MoviesCode1
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
A Hybrid System of Sound Event Detection Transformer and Frame-wise Model for DCASE 2022 Task 4Code1
Optimizing Temporal Resolution Of Convolutional Recurrent Neural Networks For Sound Event Detection—0
Multi-encoder attention-based architectures for sound recognition with partial visual assistance—0
Impact of temporal resolution on convolutional recurrent networks for audio tagging and sound event detection—0
Binaural Signal Representations for Joint Sound Event Detection and Acoustic Scene Classification—0
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
Multitask vocal burst modeling with ResNets and pre-trained paralinguistic Conformers—0
Frequency Dependent Sound Event Detection for DCASE 2022 Challenge Task 4Code1
Adaptive Few-Shot Learning Algorithm for Rare Sound Event Detection—0
Frequency Dynamic Convolution: Frequency-Adaptive Pattern Recognition for Sound Event DetectionCode1
Selective Pseudo-labeling and Class-wise Discriminative Fusion for Sound Event Detection—0
Nonverbal Sound Detection for Disordered Speech—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