Abstract
♪ Automatic violin fingering estimation
This research was carried out by Ms Nagata, who completed her master's degree in 2014, and Ms Watanabe, who graduated from the undergraduate programme in 2017. This research is characterised by its ability to estimate the appropriate fingering according to the performer's level of proficiency. Fingering refers to the grip used when playing a musical instrument, and in the case of a violin, it corresponds to which finger is used to hold down which string. The correct fingering on the violin depends on the skill level of the player, so there are several fingerings that can produce the same note. For example, at beginner level, the simplest fingering is appropriate, but as the player progresses, fingerings are used that are not only playable but also appropriate for expressing performance (e.g. different tones for different strings, vibrato, etc.). The purpose of this study is to determine the appropriate fingering for these proficiency levels from arbitrary scores.
In order to accommodate different levels of ability, it is necessary not only to determine fingerings that are playable and avoid unnatural movements, but also to make decisions based on performance expression. Therefore, we focus on performance indicator symbols other than notes in the score and model the relationship between the score and fingerings using a conditional probability field (CRF), which is one of the probabilistic models, to obtain a fingering estimation model from fingerings data.By modelling the relationship between the notation and fingerings using a conditional probability field (CRF), which is one of the probabilistic models, a fingering estimation model can be obtained from fingerings data in a music book by learning.
♪ Contrabass performance motion generation
This research was undertaken by Mr. Shirai, a master's course graduate in 2022. The objective of this research is to generate a 3-D model of a contrabass player's playing motion (3-D trajectory of the upper body's physical feature points) when playing a given score. It is expected that the 3D model will be useful for performance training for beginners and for creating a virtual performer by combining it with technology for generating performance expressions.
Publications
- Wakana Nagata, Shinji Sako, and Tadashi Kitamura, "Violin Fingering Estimation According to Skill Level based on Hidden Markov Model", Joint conference of 40th ICMC (International Computer Music Conference) and 11th SMC (Sound & Music Computing conference), pp. 1233–1238, Sep. 2014. [PDF]
- Shinji Sako, Wakana Nagata, and Tadashi Kitamura, "Violin fingering estimation according to the performer's skill level based on conditional random field", Proc. of HCII 2015, Human-Computer Interaction: Interaction Technologies, LNCS 9170, pp.485–494, Aug. 2015. [DOI]
- Takeru Shirai, and Shinji Sako, "3D skeleton motion generation of double bass from musical score", 15th International Symposium on Computer Music Multidisciplinary Research (CMMR), pp.41–46, Nov. 2021. [PDF]