In this notebook, we attempt to classify music signals for which we have two representations ; MFCCs (https://en.wikipedia.org/wiki/Mel-frequency_cepstrum) and mel-spectograms using neural networks in Pytorch.We start with a FNN and then proceed to a CNN experimenting on optimizers,activation functions, learning rate schedulers,pooling and padding,dropout,early stopping and batch normalization.Our best model presents 79.8% accuracy on test set.
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Classification of mel-spectorams and MFCCs into music genres using FNNs and CNNs.
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