Environmental Sound Classification
23 papers with code • 3 benchmarks • 6 datasets
Classification of Environmental Sounds. Most often sounds found in Urban environments. Task related to noise monitoring.
Benchmarks
These leaderboards are used to track progress in Environmental Sound Classification
| Trend | Dataset | Best Model | Paper | Code | Compare |
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ESC-50
UrbanSound8K
FSD50K
SONYC-UST-V2
ESC50
Latest papers with no code
Synthesizing Soundscapes: Leveraging Text-to-Audio Models for Environmental Sound Classification
This study analyzes the performance of two different environmental classification systems when data generated from text-to-audio models is used for training.
Mixer is more than just a model
In the field of computer vision, MLP-Mixer is noted for its ability to extract data information from both channel and token perspectives, effectively acting as a fusion of channel and token information.
Focal Modulation Networks for Interpretable Sound Classification
The increasing success of deep neural networks has raised concerns about their inherent black-box nature, posing challenges related to interpretability and trust.
EchoVest: Real-Time Sound Classification and Depth Perception Expressed through Transcutaneous Electrical Nerve Stimulation
EchoVest also provides various features, including sound localization, sound classification, noise reduction, and depth perception.
Improved Zero-Shot Audio Tagging & Classification with Patchout Spectrogram Transformers
Standard machine learning models for tagging and classifying acoustic signals cannot handle classes that were not seen during training.
Responding to Challenge Call of Machine Learning Model Development in Diagnosing Respiratory Disease Sounds
Support vector machine (SVM) with radial basis function (RBF) kernels, ensemble aggregation and decision tree classification methods were used as classification techniques.
EnvGAN: Adversarial Synthesis of Environmental Sounds for Data Augmentation
The research in Environmental Sound Classification (ESC) has been progressively growing with the emergence of deep learning algorithms.
An Ensemble of Convolutional Neural Networks for Audio Classification
The best performing ensembles combining data augmentation techniques with different signal representations are compared and shown to outperform the best methods reported in the literature on these datasets.
Environmental Sound Classification with Parallel Temporal-spectral Attention
Convolutional neural networks (CNN) are one of the best-performing neural network architectures for environmental sound classification (ESC).
Detection of Adversarial Attacks and Characterization of Adversarial Subspace
Adversarial attacks have always been a serious threat for any data-driven model.
