A new physical sensor based on neural network for musical expressivity

In this paper, we present an innovative physical sensor interface based on neural network that allows an electronic music composer to plan and conduct the musical expressivity of a performer. For musical expressivity we mean all those execution techniques and modalities that a performer has to follow in order to satisfy common musical aesthetics. The proposed sensor interface is composed by a gestural transducer, that measure motion acceleration and angular velocity, and a mapping module, that transform few physical measured parameters into a lot of specific sound synthesis parameters. It is able to transform six physical input parameters in seventeen sound synthesis parameters. In this work, we focus our attention on mapping strategies based on Neural Network to solve the problem of electronic music expressivity.