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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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 71–80 of 132 papers

Title	Date	Tasks	Status	Hype
Low-complexity acoustic scene classification for multi-device audio: analysis of DCASE 2021 Challenge systems	May 28, 2021	Acoustic Scene ClassificationQuantization	CodeCode Available	0
Receptive Field Regularization Techniques for Audio Classification and Tagging with Deep Convolutional Neural Networks	May 26, 2021	Acoustic Scene ClassificationAudio Classification	CodeCode Available	1
Spectrum Correction: Acoustic Scene Classification with Mismatched Recording Devices	May 25, 2021	Acoustic Scene ClassificationClassification	CodeCode Available	1
Attentive max feature map and joint training for acoustic scene classification	Apr 15, 2021	Acoustic Scene ClassificationMulti-Task Learning	—Unverified	0
An Analysis of State-of-the-art Activation Functions For Supervised Deep Neural Network	Apr 5, 2021	Acoustic Scene ClassificationClassification	—Unverified	0
SpecAugment++: A Hidden Space Data Augmentation Method for Acoustic Scene Classification	Mar 31, 2021	Acoustic Scene ClassificationData Augmentation	—Unverified	0
Environmental sound analysis with mixup based multitask learning and cross-task fusion	Mar 30, 2021	Acoustic Scene ClassificationClassification	—Unverified	0
Low-Complexity Models for Acoustic Scene Classification Based on Receptive Field Regularization and Frequency Damping	Nov 5, 2020	Acoustic Scene ClassificationScene Classification	CodeCode Available	1
A Two-Stage Approach to Device-Robust Acoustic Scene Classification	Nov 3, 2020	Acoustic Scene ClassificationClassification	CodeCode Available	1
DCASENET: A joint pre-trained deep neural network for detecting and classifying acoustic scenes and events	Sep 21, 2020	Acoustic Scene ClassificationAudio Tagging	CodeCode Available	1

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All datasets CochlScene DCASE 2019 Mobile TAU Urban Acoustic Scenes 2019 TUT Acoustic Scenes 2017 TUT Urban Acoustic Scenes 2018

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Audio Flamingo	1:1 Accuracy	0.83	—	Unverified
2	Qwen-Audio	1:1 Accuracy	0.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Basic + Spectrum Correction	Accuracy	70.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Two-stage ensemble system	1:1 Accuracy	81.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Qwen-Audio	1:1 Accuracy	0.65	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ERGL: event relational graph representation learning	Acc	78.1	—	Unverified