SOTAVerified

Acoustic Scene Classification

The goal of acoustic scene classification is to classify a test recording into one of the provided predefined classes that characterizes the environment in which it was recorded.

Source: DCASE 2019 Source: DCASE 2018

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 31–40 of 132 papers

TitleStatusHype
Data Efficient Acoustic Scene Classification using Teacher-Informed Confusing Class Instruction—0
A punishment voting algorithm based on super categories construction for acoustic scene classification—0
Acoustic Scene Classification—0
Compressing audio CNNs with graph centrality based filter pruning—0
An evaluation of data augmentation methods for sound scene geotagging—0
Channel Compression: Rethinking Information Redundancy among Channels in CNN Architecture—0
An Analysis of State-of-the-art Activation Functions For Supervised Deep Neural Network—0
Acoustic Scene Classification using Audio Tagging—0
Creating a Good Teacher for Knowledge Distillation in Acoustic Scene Classification—0
Capturing scattered discriminative information using a deep architecture in acoustic scene classification—0
Show:102550
← PrevPage 4 of 14Next →
All datasetsCochlSceneDCASE 2019 MobileTAU Urban Acoustic Scenes 2019TUT Acoustic Scenes 2017TUT Urban Acoustic Scenes 2018

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Audio Flamingo1:1 Accuracy0.83—Unverified
2Qwen-Audio1:1 Accuracy0.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Basic + Spectrum CorrectionAccuracy70.4—Unverified
#ModelMetricClaimedVerifiedStatus
1Two-stage ensemble system1:1 Accuracy81.9—Unverified
#ModelMetricClaimedVerifiedStatus
1Qwen-Audio1:1 Accuracy0.65—Unverified
#ModelMetricClaimedVerifiedStatus
1ERGL: event relational graph representation learningAcc78.1—Unverified