I have isolated preprocessed musical notes with a transformation function, CQT.
This function returns each note to me as a two-dimensional shape matrix (252, n), where n is variable and depends on the audio time. Each row, represents a note, so, each note is an input.
Each of these preprocessed notes are represented with a target, shape matrices (88,n), represented with 0s. Each row of targets represent the target of a row in the input data.
If my note is 0, the first row is filled with 1 and the rest with 0. And if the note is 3, the third row is filled with 1 and the rest with 0.
After this, I have concatenated all notes and all targets and inputs and transposed them.
Each input of 252 is related to a target of 88.
I try to make the neural network output learn which note is being introduced.
If something is not clear, I can try to explain it in another way.