The invention discloses a music model training method. The music model training method comprises the following steps: acquiring a
MIDI music
data set, wherein the
MIDI music
data set comprises a plurality of
MIDI music scores; extracting the
feature vector of each MIDI music
score; inputting the feature vectors into a structured
support vector machine for training, so that a music model is obtained, the step specifically comprises the following substeps: constructing a
discrimination function f(x;w), wherein x is a
feature vector, w is a parameter vector, carrying out outputting by adopting the
data value (with the calculation formula shown in the description) of the maximal
discrimination function f(x;w) as the predicted value, calculating the predicted value and the true value accordingto a preset
loss function (shown in the description), wherein P is the probability distribution of data, which is replaced with the empirical risk (shown in the description) obtained through calculation with the trained sample data, solving the unique parameter vector
omega by adopting the optimizing formula (as shown in the description) of SVM, so that the empirical risk (shown in the description) obtained through the trained sample data is 0, solving the
discrimination function f(x;
omega), and finally, outputting the music
time sequence. The invention further provides a music creation method, devices, a terminal and a storage medium. In the technical scheme,
artificial intelligence is used for music model training for the first time, for the trained music model, the
feature extraction capacity of the MIDI music
score can be improved.