New Sensors and Pattern Recognition Techniques for String Instruments

Pressure, motion, and gesture are important parameters in musical instrument playing. Pressure sensing allows to interpret complex hidden forces, which appear during playing a musical instrument. The combination of our new sensor setup with pattern recognition techniques like the lately developed ordered means models allows fast and precise recognition of highly skilled playing techniques. This includes left and right hand analysis as well as a combination of both. In this paper we show bow position recognition for string instruments by means of support vector regression machines on the right hand finger pressure, as well as bowing recognition and inaccurate playing detection with ordered means models. We also introduce a new left hand and chin pressure sensing method for coordination and position change analysis. Our methods in combination with our audio, video, and gesture recording software can be used for teaching and exercising. Especially studies of complex movements and finger force distribution changes can benefit from such an approach. Practical applications include the recognition of inaccuracy, cramping, or malposition, and, last but not least, the development of augmented instruments and new playing techniques.

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