I am doing a study for the classification of musical genres using deep learning techniques. The work consists of making a classification using an LSTM model.
I am using GTZAN as a data set, and preprocessing them using Librosa. This way I obtain the spectral characteristics, specifically: Spectral centroid.
My input data has the following size: X_train (750, 20, 1249).
My model is:
model = Sequential () model.add (LSTM (units = 512, return_sequences = True, input_shape = (X_train.shape , X_train.shape ))) model.add (LSTM (units = 32, return_sequences = False)) model.add (Dense (units = 10, activation = 'softmax')) model.compile (loss = losses.categorical_crossentropy, optimizer = Adam (), metrics = ['accuracy'])
I scale also my data using MinMaxScaler.
I appreciate any help. Thank you.