Research Article
The Speckled Cellist : Classification of Cello Bowing Techniques using the Orient Specks
@ARTICLE{10.4108/eai.28-9-2015.2261477, author={Debadri Mukherjee and DK Arvind}, title={The Speckled Cellist : Classification of Cello Bowing Techniques using the Orient Specks}, journal={EAI Endorsed Transactions on Pervasive Health and Technology}, volume={2}, number={6}, publisher={ACM}, journal_a={PHAT}, year={2015}, month={12}, keywords={cello bowing, wearable sensors, wireless inertial-magnetic sensors, orient specks, svm classifier}, doi={10.4108/eai.28-9-2015.2261477} }- Debadri Mukherjee
DK Arvind
Year: 2015
The Speckled Cellist : Classification of Cello Bowing Techniques using the Orient Specks
PHAT
EAI
DOI: 10.4108/eai.28-9-2015.2261477
Abstract
Cello bowing techniques are classified by applying supervised machine learning methods to sensor data from two inertial sensors called the Orient specks – one worn on the playing wrist and the other attached to the frog of the bow. Twelve different bowing techniques were considered, including variants on a single string and across multiple strings. Results are presented for the classification of these twelve techniques when played singly, and in combination during improvisational play. The results demonstrated that even when limited to two sensors, classification accuracy in excess of 95% was obtained for the individual bowing styles, with the added advantages of a minimalist approach.
Copyright © 2015 D. K. Arvind and D. Mukherjee, licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
