Violin fingering estimation according to the performer’s skill level based on conditional random field

Abstract

In this paper, we propose a method that estimates appropriate violin fingering according to the performer’s skill level based on a conditional random field (CRF). A violin is an instrument that can produce the same pitch for different fingering patterns, and these patterns depend on skill level. We previously proposed a statistical method for violin fingering estimation, but that method required a certain amount of training data in the form of fingering annotation corresponding to each note in the music score. This was a major issue of our previous method, because it takes time and effort to produce the annotations. To solve this problem, we proposed a method to automatically generate training data for a fingering model using existing violin textbooks. Our experimental results confirmed the effectiveness of the proposed method.