Data-Driven Visual Reflection on Music Instrument Practice

TL;DR

This paper introduces a data-driven visualization approach for long-term music instrument practice, enabling musicians to analyze progress and trends through recorded sessions, inspired by fitness tracking methods.

Contribution

It presents a novel visualization framework for analyzing long-term practice data, supported by user feedback from guitarists over three months.

Findings

Effective visualization designs identified for practice analysis

Musicians found data-driven feedback useful for progress tracking

Feasibility demonstrated with real user data over months

Abstract

We propose a data-driven approach to music instrument practice that allows studying patterns and long-term trends through visualization. Inspired by life logging and fitness tracking, we imagine musicians to record their practice sessions over the span of months or years. The resulting data in the form of MIDI or audio recordings can then be analyzed sporadically to track progress and guide decisions. Toward this vision, we started exploring various visualization designs together with a group of nine guitarists, who provided us with data and feedback over the course of three months.