Deep Convolutional Neural Networks For Environmental Sound Classification

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Abstract: We propose a model to classify environmental sounds such as People Sounds, Vehicles Sounds, Siren Sounds, Horn, Engine Sounds. We perform Data Augmentation techniques to extract best features from the given audio to classify which class of sound. Our deep convolutional neural network architecture uses stacked convolutional and pooling layers to extract highlevel feature representations from spectrogram-like features from the given input.