A data-driven approach to violin making

Abstract Of all the characteristics of a violin, those that concern its shape are probably most important ones, as violin maker has complete control over them. Contemporary making, however, is still based more on tradition than understanding, and definitive scientific study specific relations exist between vibrational properties yet to come sorely missed. In this article, using standard statistical learning tools, we show modal frequencies tops can, in fact, be predicted from geometric parameters, artificial intelligence can successfully applied traditional making. We also how vary with thicknesses plate (a process often referred tuning ) discuss complexity dependency. Finally, propose predictive tool for tuning, which takes into account material parameters.