A Physical Intelligent Instrument using Recurrent Neural Networks

Torgrim Rudland Næss, and Charles Patrick Martin

Proceedings of the International Conference on New Interfaces for Musical Expression

• Year: 2019
• Location: Porto Alegre, Brazil
• Pages: 79–82
• DOI: 10.5281/zenodo.3672874 (Link to paper)
• PDF link

Abstract:

This paper describes a new intelligent interactive instrument, based on an embedded computing platform, where deep neural networks are applied to interactive music generation. Even though using neural networks for music composition is not uncommon, a lot of these models tend to not support any form of user interaction. We introduce a self-contained intelligent instrument using generative models, with support for real-time interaction where the user can adjust high-level parameters to modify the music generated by the instrument. We describe the technical details of our generative model and discuss the experience of using the system as part of musical performance.

Citation:

BibTeX Entry:

  @inproceedings{Næss2019,
 abstract = {This paper describes a new intelligent interactive instrument, based on an embedded computing platform, where deep neural networks are applied to interactive music generation. Even though using neural networks for music composition is not uncommon, a lot of these models tend to not support any form of user interaction. We introduce a self-contained intelligent instrument using generative models, with support for real-time interaction where the user can adjust high-level parameters to modify the music generated by the instrument. We describe the technical details of our generative model and discuss the experience of using the system as part of musical performance.},
 address = {Porto Alegre, Brazil},
 author = {Torgrim Rudland Næss and Charles Patrick Martin},
 booktitle = {Proceedings of the International Conference on New Interfaces for Musical Expression},
 doi = {10.5281/zenodo.3672874},
 editor = {Marcelo Queiroz and Anna Xambó Sedó},
 issn = {2220-4806},
 month = {June},
 pages = {79--82},
 publisher = {UFRGS},
 title = {A Physical Intelligent Instrument using Recurrent Neural Networks},
 url = {http://www.nime.org/proceedings/2019/nime2019_paper016.pdf},
 year = {2019}
}