Real-Time Gesture Classification on an Augmented Acoustic Guitar using AI to Improve Extended-Range and Percussive Solo Playing
The aim of this project is to investigate and implement a system of real-time classification of player-to-instrument interactions on the acoustic guitar, focussing on the gesture vocabulary that is typical of percussive fingerstyle playing. Such a system will be used as a platform for augmentation of the acoustic guitar, allowing the player to reach the bass range effectively and play more complete percussive parts.
The study will focus on finding and describing the details of the gesture vocabulary typical of the percussive fingerstyle player. It will then try to match it to a network of sensors and a set of AI technologies which will perform an optimal real-time classification of the interactions. The potential for augmentation will finally be investigated with aspiring and professional players of the genre, in order to create an instrument that both lowers the entry barrier for a complete musical performance on the acoustic guitar, and expands the performer's possibilities.
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