Neural Music Synthesis for Flexible Timbre Control [article]

Jong Wook Kim, Rachel Bittner, Aparna Kumar, Juan Pablo Bello
2018 arXiv   pre-print
The recent success of raw audio waveform synthesis models like WaveNet motivates a new approach for music synthesis, in which the entire process --- creating audio samples from a score and instrument information --- is modeled using generative neural networks. This paper describes a neural music synthesis model with flexible timbre controls, which consists of a recurrent neural network conditioned on a learned instrument embedding followed by a WaveNet vocoder. The learned embedding space
more » ... sfully captures the diverse variations in timbres within a large dataset and enables timbre control and morphing by interpolating between instruments in the embedding space. The synthesis quality is evaluated both numerically and perceptually, and an interactive web demo is presented.
arXiv:1811.00223v1 fatcat:z726pibdujeq3mwfdkqjdf7ko4