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

Showing 126132 of 132 papers

TitleStatusHype
Deep Within-Class Covariance Analysis for Robust Audio Representation Learning0
A Hybrid Approach with Multi-channel I-Vectors and Convolutional Neural Networks for Acoustic Scene Classification0
Hierarchical learning for DNN-based acoustic scene classification0
Classifying Variable-Length Audio Files with All-Convolutional Networks and Masked Global PoolingCode0
Label Tree Embeddings for Acoustic Scene Classification0
Acoustic Scene Classification0
Automatic Monitoring of Activities of Daily Living based on Real-life Acoustic Sensor Data: a preliminary study0
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Benchmark Results

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