Performing Structured Improvisations with pre-trained Deep Learning Models
Sound
2019-05-01 v1 Machine Learning
Audio and Speech Processing
Abstract
The quality of outputs produced by deep generative models for music have seen a dramatic improvement in the last few years. However, most deep learning models perform in "offline" mode, with few restrictions on the processing time. Integrating these types of models into a live structured performance poses a challenge because of the necessity to respect the beat and harmony. Further, these deep models tend to be agnostic to the style of a performer, which often renders them impractical for live performance. In this paper we propose a system which enables the integration of out-of-the-box generative models by leveraging the musician's creativity and expertise.
Cite
@article{arxiv.1904.13285,
title = {Performing Structured Improvisations with pre-trained Deep Learning Models},
author = {Pablo Samuel Castro},
journal= {arXiv preprint arXiv:1904.13285},
year = {2019}
}