A data-driven approach to violin making

Abstract

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

Compositional and Morphological Comparison among Three Coeval Violins Made by Giuseppe Guarneri “del Gesù” in 1734

“…The outline plots (discussed in Section 3.2) are not smoothed, as the variations are smaller than the line thickness at the scale we plotted. All the tools used are discussed in more detail in [30,31].…”

A Review of Finite Element Studies in String Musical Instruments

“…Recently, Gonzalez et al [52,53] demonstrated that the modal frequencies of the violin soundboards can be predicted by an artificial intelligence neural network based on their geometric parameters; furthermore, it is observed that this approach can be successfully adopted by traditional violinmakers. Moreover, the studies of Lu [47] and Kaselouris et al [54] explored the possibility of using composite materials to substitute the traditional wood material of the top plates.…”

A Physics-Informed Neural Network Approach for Nearfield Acoustic Holography

“…We varied the dimensions and the BCs of the aluminum rectangular plate to build an extensive dataset, whereas in the violin plate dataset, the outline of the plate was modified according to [ 43 ].…”

“…As for the violin plate dataset, we simulated 1568 different synthetic violin top plates with variable outline. Authors in [ 43 ] described 20 different parameters, which enable the complete definition of a violin top plate geometry, i.e., shape and dimensions. In [ 43 ], shape parameters are sampled from Gaussian distributions centered around the nominal value of a reference violin (based on a Stradivarius instrument).…”

“…Authors in [ 43 ] described 20 different parameters, which enable the complete definition of a violin top plate geometry, i.e., shape and dimensions. In [ 43 ], shape parameters are sampled from Gaussian distributions centered around the nominal value of a reference violin (based on a Stradivarius instrument). Thanks to this approach, we used different violin-like geometries with parametric outlines in order to ease a generalization on the 3D shapes.…”