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Magenta.js: A JavaScript API for Augmenting Creativity with Deep Learning

Curtis Hawthorne
Ian Simon
Joint Workshop on Machine Learning for Music (ICML) (2018)

Abstract

New methods for modeling musical scores, often based on deep learning, have made it possible to automatically generate ever more convincing compositions. However, to enhance the creativity of a new generation of artists, they must be empowered to easily play and experiment with these models on their own terms. Application developers are already imagining ways to apply their design expertise to this new class of AI technologies but often lack a sufficient background in machine learning. Magenta.js is a new open source library with a simple JavaScript API intended to bridge this gap by abstracting away technical details, making it easier than ever for app developers to create new interfaces to generative models. Furthermore, because it is easily extensible, we hope that Magenta.js can foster a connection between the broader research community and creative developers through contributions from both groups. Finally, Magenta.js will open up the possibility for a new type of compositional tool that adapts to user preferences and behaviors in real-time. Code and documentation are available online at https://goo.gl/magenta/js.