Audio representation for environmental sound classification using convolutional neural networks
A convolutional neural network (CNN) training framework is described and implemented. The framework is used to train and evaluate an audio classification system, focused on evaluating differences in audio representation. The dataset used is ESC-50, containing 50 different classes of audio. We used SBCNN, a promising architecture suited for embedded systems because of its relatively small size. Sev