Classification of Environmental Sounds. Most often sounds found in Urban environments. Task related to noise monitoring.
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We show that the improved performance stems from the combination of a deep, high-capacity model and an augmented training set: this combination outperforms both the proposed CNN without augmentation and a "shallow" dictionary learning model with augmentation.
Noise monitoring using Wireless Sensor Networks are being applied in order to understand and help mitigate these noise problems.
#3 best model for Environmental Sound Classification on UrbanSound8k
End-to-end neural network based approaches to audio modelling are generally outperformed by models trained on high-level data representations.
We have evaluated the MCLNN performance using the Urbansound8k dataset of environmental sounds.