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Ludwig van Beethoven composed his symphonies between 1799 and 1825, when hewas writing his Tenth symphony. As we dispose of a great amount of databelonging to his work, the purpose of this paper is to investigate thepossibility of extracting patterns on his compositional model from symbolicdata and generate what would have been his last symphony, the Tenth. A neuralnetwork model has been built based on the Long Short-Therm Memory (LSTM) neuralnetworks. After training the model, the generated music has been analysed bycomparing the input data with the results, and establishing differences betweenthe generated outputs based on the training data used to obtain them. Thestructure of the outputs strongly depends on the symphonies used to train thenetwork.

An approach to Beethoven's 10th Symphony