phat 16(6): e3

Research Article

The Speckled Cellist : Classification of Cello Bowing Techniques using the Orient Specks

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  • @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
Debadri Mukherjee1, DK Arvind1,*
  • 1: University of Edinburgh
*Contact email: dka@inf.ed.ac.uk

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.