Augmenting Sheet Music with Rhythmic Fingerprints

TL;DR

This paper introduces rhythmic fingerprints as an augmentation to traditional sheet music, enhancing rhythm analysis by making patterns more accessible, especially for novices, without replacing the established notation.

Contribution

It presents a novel rhythmic fingerprint visualization that complements sheet music, aiding rhythm comprehension and pattern recognition for both experts and novices.

Findings

Rhythmic fingerprints improve pattern recognition for novices.

Experts can identify rhythmic patterns more easily with the augmentation.

User study confirms the effectiveness of the visualization.

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.