Bach Style Music Authoring System based on Deep Learning
This addresses the problem of automated music composition in a specific classical style for applications in creative AI, though it appears incremental.
The paper tackled generating Bach-style music using deep learning, achieving results where AI-created music was difficult for ordinary people to distinguish from Bach's original works.
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.