MelodyVis: Visual Analytics for Melodic Patterns in Sheet Music
Matthias Miller, Daniel F\"urst, Maximilian T. Fischer, Hanna, Hauptmann, Daniel Keim, Mennatallah El-Assady

TL;DR
MelodyVis is a visual analytics tool that helps musicologists explore and identify melodic patterns in digital sheet music more effectively than manual or fully automated methods.
Contribution
The paper introduces MelodyVis, a novel visual system with interactive operators for melodic pattern analysis, developed in collaboration with musicology experts.
Findings
Participants identified twice as many patterns with operators enabled.
MelodyVis improved pattern interpretation and analysis efficiency.
User study confirmed the system's usefulness and usability.
Abstract
Manual melody detection is a tedious task requiring high expertise level, while automatic detection is often not expressive or powerful enough. Thus, we present MelodyVis, a visual application designed in collaboration with musicology experts to explore melodic patterns in digital sheet music. MelodyVis features five connected views, including a Melody Operator Graph and a Voicing Timeline. The system utilizes eight atomic operators, such as transposition and mirroring, to capture melody repetitions and variations. Users can start their analysis by manually selecting patterns in the sheet view, and then identifying other patterns based on the selected samples through an interactive exploration process. We conducted a user study to investigate the effectiveness and usefulness of our approach and its integrated melodic operators, including usability and mental load questions. We compared…
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Taxonomy
TopicsMusic Technology and Sound Studies · Music and Audio Processing · Diverse Musicological Studies
