Violin Timbre Navigator: Real-Time Visual Feedback of Violin Bowing Based on Audio Analysis and Machine Learning

Bowing is the main control mechanism in sound production during a violin performance. The balance among bowing parameters such as acceleration, force, velocity or bow-bridge distance are continuously determining the characteristics of the sound. However, in traditional music pedagogy, approaches to teaching the mechanics of bowing are based on subjective and vague perception, rather than on accurate understanding of the principles of movement bowing. In the last years, advances in technology has allowed to measure bowing parameters in violin performances. However, sensing systems are generally very expensive, intrusive and require for very complex and time consuming setups, which makes it impossible to bring them into a classroom environment. Here, we propose an algorithm that is able to estimate bowing parameters from audio analysis in real-time, requiring just a microphone and a simple calibration process. Additionally, we present the Violin Palette, a prototype that uses the reported algorithm and presents bowing information in an intuitive way.