Bach Style Music Authoring System based on Deep Learning
  With the continuous improvement in various aspects in the field of artificial
intelligence, the momentum of artificial intelligence with deep learning
capabilities into the field of music is coming. The research purpose of this
paper is to design a Bach style music authoring system based on deep learning.
We use a LSTM neural network to train serialized and standardized music feature
data. By repeated experiments, we find the optimal LSTM model which can
generate imitation of Bach music. Finally the generated music is
comprehensively evaluated in the form of online audition and Turing test. The
repertoires which the music generation system constructed in this article are
very close to the style of Bach's original music, and it is relatively
difficult for ordinary people to distinguish the musics Bach authored and AI
created.
