Abstract
We present in this paper PerformacnceNet, a neural network model we proposed recently to achieve
score-to-audio music generation. The model learns
to convert a music piece from the symbolic domain
to the audio domain, assigning performance-level
attributes such as changes in velocity automatically
to the music and then synthesizing the audio. The
model is therefore not just a neural audio synthesizer, but an AI performer that learns to interpret a
musical score in its own way. The code and sample outputs of the model can be found online at
https://github.com/bwang514/PerformanceNet.
Keywords
- AI: Human-Computer Interactive Systems
- AI: Machine Learning
