SOTAVerified

Sound Event Localization and Detection

Given multichannel audio input, a sound event detection and localization (SELD) system outputs a temporal activation track for each of the target sound classes, along with one or more corresponding spatial trajectories when the track indicates activity. This results in a spatio-temporal characterization of the acoustic scene that can be used in a wide range of machine cognition tasks, such as inference on the type of environment, self-localization, navigation without visual input or with occluded targets, tracking of specific types of sound sources, smart-home applications, scene visualization systems, and audio surveillance, among others.

Papers

Showing 6165 of 65 papers

TitleStatusHype
Squeeze-and-Excite ResNet-Conformers for Sound Event Localization, Detection, and Distance Estimation for DCASE 2024 Challenge0
Stereo sound event localization and detection based on PSELDnet pretraining and BiMamba sequence modeling0
SwG-former: A Sliding-Window Graph Convolutional Network for Simultaneous Spatial-Temporal Information Extraction in Sound Event Localization and Detection0
TASK3 DCASE2021 Challenge: Sound event localization and detection using squeeze-excitation residual CNNs0
Text-Queried Target Sound Event Localization0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AVC-FillerNetevent-based F1 score92.8Unverified
2VC-FillerNetevent-based F1 score71Unverified
#ModelMetricClaimedVerifiedStatus
1Baseline (MIC)Class-dependent localization error32.2Unverified
2Baseline (FOA)Class-dependent localization error29.3Unverified
#ModelMetricClaimedVerifiedStatus
1DualQSELD-TCN (parallel)SELD score0.32Unverified
#ModelMetricClaimedVerifiedStatus
1STL-SNNaccuracy98.4Unverified
#ModelMetricClaimedVerifiedStatus
1SALSA-FOAER≤20°0.38Unverified