CorpusVis: Visual Analysis of Digital Sheet Music Collections

Abstract

Manually investigating sheet music collections is challenging for music analysts due to the magnitude and complexity of underlying features, structures, and contextual information. However, applying sophisticated algorithmic methods would require advanced technical expertise that analysts do not necessarily have. Bridging this gap, we contribute CorpusVis, an interactive visual workspace, enabling scalable and multi-faceted analysis. Our proposed visual analytics dashboard provides access to computational methods, generating varying perspectives on the same data. The proposed application uses metadata including composers, type, epoch, and low-level features, such as pitch, melody, and rhythm. To evaluate our approach, we conducted a pair-analytics study with nine participants. The qualitative results show that CorpusVis supports users in performing exploratory and confirmatory analysis, leading them to new insights and findings. In addition, based on three exemplary workflows, we demonstrate how to apply our approach to different tasks, such as exploring musical features or comparing composers.

ChoreoVis: Planning and Assessing Formations in Dance Choreographies

“…Different from other visual representations of musical data [KKM*20], the alignment of choreographic formations with the musical part in our approach takes place on an abstract level. The realization of this sequential aspect and the alignment of the choreography to it is therefore realized in a more abstract way than usual when supporting the analysis of sheet music [MRKEA22], composing music [RHWS22], music recommendation [SI11], or practicing musical performances [HS22]. Our approach uses discrete modeling [AMST11] of music (play time) in a linear timeline representation.…”

Augmenting Digital Sheet Music through Visual Analytics

“…The notational complexity of the musical dimensions [MHK*18] requires reading proficiency to understand the underlying musical concepts. Below, we introduce the musical features from the smallest unit to compound concepts including harmony , rhythm and melody .…”

“…Such manual analysis tasks are segmentation, structure analysis [LJ83b], annotation and comparison of sheet music. Without the help of additional tools, these tasks are time‐consuming and tedious due to the visual complexity of CMN [MHK*18]. Close reading is restricted to CMN, which does not readily convey an overview of larger sections.…”

“…Thus, analyzing patterns in sheet music facilitates the study of a composer's intentions and the structural elements inherent in a piece, while audio analysis involves the interpretation of a musician, which may introduce deviations or inaccuracies [19]. Moreover, sheet music captures essential musical elements, such as pitch, rhythm, dynamics, and articulation [49], in a visually accessible format that simplifies pattern identification and comparison across different compositions from a larger corpus [50]. The notational unambiguity of sheet music enables researchers to examine subtle variations in melodic and harmonic structures and uncover relationships between different pieces or composers that may not be readily apparent in audio recordings.…”