Latent Space Oddity: Exploring Latent Spaces to Design Guitar Timbres
arXiv:2010.15989
Abstract
We introduce a novel convolutional network architecture with an interpretable latent space for modeling guitar amplifiers. Leveraging domain knowledge of popular amplifiers spanning a range of styles, the proposed system intuitively combines or subtracts characteristics of different amplifiers, allowing musicians to design entirely new guitar timbres.
3 pages, 1 figure. To appear in the 2020 NeurIps Workshop on Machine Learning for Creativity and Design