Environmental Sound Classification
3 papers with code ·
Audio
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Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound Classification
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.
Utilizing Domain Knowledge in End-to-End Audio Processing
End-to-end neural network based approaches to audio modelling are generally outperformed by models trained on high-level data representations.
Masked Conditional Neural Networks for Environmental Sound Classification
We have evaluated the MCLNN performance using the Urbansound8k dataset of environmental sounds.