Music FaderNets is a controllable MIDI generation framework that models high-level musical qualities, such as emotional attributes like arousal. Drawing inspiration from the concept of sliding faders on a mixing console, the model offers intuitive and continuous control over these characteristics. Given an input MIDI, Music FaderNets can produce multiple variations with different levels of arousal, adjusted according to the position of the fader.
Year: 2020
Website: https://music-fadernets.github.io/
Input types: MIDI
Output types: MIDI
Output length:
AI Technique: VAE
Dataset: VGMIDI, Yamaha Piano-e-Competition
License type: MIT
Real time:
Free:
Open source:
Checkpoints:
Fine-tune:
Train from scratch:
Code accompanying ISMIR 2020 paper - "Music FaderNets: Controllable Music Generation Based On High-Level Features via Low-Level Feature Modelling" can be found on GitHub: https://github.com/gudgud96/music-fader-nets