  Ludwig van Beethoven composed his symphonies between 1799 and 1825, when he
was writing his Tenth symphony. As we dispose of a great amount of data
belonging to his work, the purpose of this paper is to investigate the
possibility of extracting patterns on his compositional model from symbolic
data and generate what would have been his last symphony, the Tenth. A neural
network model has been built based on the Long Short-Therm Memory (LSTM) neural
networks. After training the model, the generated music has been analysed by
comparing the input data with the results, and establishing differences between
the generated outputs based on the training data used to obtain them. The
structure of the outputs strongly depends on the symphonies used to train the
network.
