The Birl: An Electronic Wind Instrument Based on an Artificial Neural Network Parameter Mapping Structure

Jeff Snyder, and Danny Ryan

Proceedings of the International Conference on New Interfaces for Musical Expression

• Year: 2014
• Location: London, United Kingdom
• Pages: 585–588
• DOI: 10.5281/zenodo.1178939 (Link to paper)
• PDF link

Abstract:

This paper discusses the Birl, an electronic wind instrument developed by the authors. It uses artificial neural nets to apply machine learning to the mapping of fingering systems and embouchure position. The design features of the instrument are described, and the machine learning mapping strategy is discussed.

Citation:

BibTeX Entry:

  @inproceedings{jsnyder12014,
 abstract = {This paper discusses the Birl, an electronic wind instrument developed by the authors. It uses artificial neural nets to apply machine learning to the mapping of fingering systems and embouchure position. The design features of the instrument are described, and the machine learning mapping strategy is discussed.},
 address = {London, United Kingdom},
 author = {Jeff Snyder and Danny Ryan},
 booktitle = {Proceedings of the International Conference on New Interfaces for Musical Expression},
 doi = {10.5281/zenodo.1178939},
 issn = {2220-4806},
 month = {June},
 pages = {585--588},
 publisher = {Goldsmiths, University of London},
 title = {The Birl: An Electronic Wind Instrument Based on an Artificial Neural Network Parameter Mapping Structure},
 url = {http://www.nime.org/proceedings/2014/nime2014_540.pdf},
 year = {2014}
}