Augmenting Sheet Music with Rhythmic Fingerprints

Daniel Furst, Matthias Miller, Daniel A. Keim, Alexandra Bonnici, Hanna Schafer, Mennatallah El-assady

Research output: Contribution to conferencePaperAcademic

Abstract

In this paper, we bridge the gap between visualization and musicology by focusing on rhythm analysis tasks, which are tedious due to the complex visual encoding of the well-established Common Music Notation (CMN). Instead of replacing the CMN, we augment sheet music with rhythmic fingerprints to mitigate the complexity originating from the simultaneous encoding of musical features. The proposed visual design exploits music theory concepts such as the rhythm tree to facilitate the understanding of rhythmic information. Juxtaposing sheet music and the rhythmic fingerprints maintains the connection to the familiar representation. To investigate the usefulness of the rhythmic fingerprint design for identifying and comparing rhythmic patterns, we conducted a controlled user study with four experts and four novices. The results show that the rhythmic fingerprints enable novice users to recognize rhythmic patterns that only experts can identify using non-augmented sheet music.
Original languageEnglish
Pages14-23
DOIs
Publication statusPublished - Oct 2020
Event2020 IEEE 5th Workshop on Visualization for the Digital Humanities (VIS4DH) - Salt Lake City, UT, USA
Duration: 25 Oct 202025 Oct 2020

Conference

Conference2020 IEEE 5th Workshop on Visualization for the Digital Humanities (VIS4DH)
Period25/10/2025/10/20

Keywords

  • rhythmic patterns
  • rhythm visualization
  • music analysis

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