Realtime Classification of Hand-Drum Strokes

Michael Krzyzaniak, and Garth Paine

Proceedings of the International Conference on New Interfaces for Musical Expression

Abstract

Herein is presented a method of classifying hand-drum strokes in real-time by analyzing 50 milliseconds of audio signal as recorded by a contact-mic affixed to the body of the instrument. The classifier performs with an average accuracy of about 95% across several experiments on archetypical strokes, and 89% on uncontrived playing. A complete ANSI C implementation for OSX and Linux is available on the author's website.

Citation

Michael Krzyzaniak, and Garth Paine. 2015. Realtime Classification of Hand-Drum Strokes. Proceedings of the International Conference on New Interfaces for Musical Expression. DOI: 10.5281/zenodo.1179112 [PDF]

BibTeX Entry

@inproceedings{mkrzyzaniak2015,
 abstract = {Herein is presented a method of classifying hand-drum strokes in real-time by analyzing 50 milliseconds of audio signal as recorded by a contact-mic affixed to the body of the instrument. The classifier performs with an average accuracy of about 95% across several experiments on archetypical strokes, and 89% on uncontrived playing. A complete ANSI C implementation for OSX and Linux is available on the author's website.},
 address = {Baton Rouge, Louisiana, USA},
 author = {Michael Krzyzaniak and Garth Paine},
 booktitle = {Proceedings of the International Conference on New Interfaces for Musical Expression},
 doi = {10.5281/zenodo.1179112},
 editor = {Edgar Berdahl and Jesse Allison},
 issn = {2220-4806},
 month = {May},
 pages = {400--403},
 publisher = {Louisiana State University},
 title = {Realtime Classification of Hand-Drum Strokes},
 url = {http://www.nime.org/proceedings/2015/nime2015_147.pdf},
 year = {2015}
}