Prediction of lute acoustic quality based on soundboard vibration performance using multiple choice model

Abstract

The vibrational performance of wood materials critical affects the acoustic quality of a lute. The purpose of this research was to apply a multiple choice model to predict the quality of musical instruments based on data on lute soundboard vibrational properties of Paulownia wood. In the lute production, lute material selection mainly depends on the subjective evaluation of technicians, which is not only inefficient, but inaccurate. In this study, nine lutes were fabricated. Using the multiple selection model, the lute tone quality was predicted by the soundboard wood vibration data. Compared with the actual value, the dependent value predicted by the count of observations with the maximum probability had 22 erroneous judgments. The model precision is 87.78%. The results confirmed that the prediction model can be used as a guideline for the selection of the soundboard wood in musical instrument plants.

Research on vibration property of Picea wood for piano sound quality neural network and ant colony algorithm

“…In the past few years, a number of musicians, scientists and instrument makers have studied the microscopic properties of different wood species, laying the foundation for the selection of musical instrument sound boards. At present, the quality of soundboards depends on subjective evaluation, which is not always accurate and effective [1,2] . The knowledge in this field comes from both scientific methods and empirical methods, and sometimes, as defined by Woodhouse [3] through "lasting folk memory".…”