Augmenting Sheet Music with Rhythmic Fingerprints
September 04, 2020 Β· Declared Dead Β· π 2020 IEEE 5th Workshop on Visualization for the Digital Humanities (VIS4DH)
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Authors
Daniel FΓΌrst, Matthias Miller, Daniel Keim, Alexandra Bonnici, Hanna SchΓ€fer, Mennatallah El-Assady
arXiv ID
2009.02057
Category
cs.HC: Human-Computer Interaction
Citations
6
Venue
2020 IEEE 5th Workshop on Visualization for the Digital Humanities (VIS4DH)
Last Checked
4 months ago
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.
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