PROJECTS

[Reference /引用はこちら]
Yurina Mizuho, Riku Kitamura, Yuta Sugiura, Estimation of Violin Bow Pressure Using Photo-Reflective Sensors, In Proceedings of the 25th International Conference on Multimodal Interaction (ICMI 2023), ACM, 216–223, October 9-13, 2023, Paris, France.[DOI]

バイオリン演奏において，特に右手の運弓動作は音色を決定づける重要な要素であるが，非常に複雑で習得や再現，指導が困難である．そこで練習支援や記録を目的として，バイオリンの運弓動作の測定や分析が多く研究されてきた．本研究では運弓動作のパラメータのうち弓圧に着目する．まず弓の棒と毛の間に反射型光センサを設置し，毛の変形を計測する．次に毛の変形と弓圧の真値の対応関係から回帰モデルを学習させることで，毛の変形のみから弓圧を推定できるようになる．学習させた回帰モデルを用いて，バイオリンを弾きながらリアルタイムに弓圧を推定し，視覚的にフィードバックする例を示した．

https://www.slideshare.net/sugiuralab/estimation-of-violin-bow-pressure-using-photoreflective-sensors

The violin is one of the most popular instruments, but hard to learn. In particular, the bowing of the right hand is a crucial factor in determining the tone quality, but it is too complex to master and teach. Therefore, we focus on bow pressure, one of the parameters of bowing motion, and attempt to measure it to support practice. The proposed method uses a regression model to estimate bow pressure from bow deformation. First, the deformation of the bow hair is measured by photo-reflective sensors equipped on the bow stick. Next, the regression model is trained based on the correspondence between the bow deformation and the true value of bow pressure measured by a load cell. We also showed an example of an application for real-time bow pressure estimation and visual feedback while playing the violin.