Close reading is restricted to CMN, which does not readily convey an overview of larger sections. Without the help of additional tools, these tasks are time-consuming and tedious due to the visual complexity of CMN .
Sonic visualiser chord labelling example manual#
Such manual analysis tasks are segmentation, structure analysis , annotation and comparison of sheet music. Music analysts typically perform manual analysis of sheet music based on common music notation (CMN) that requires proficiency and years of training to understand underlying feature relationships. Besides meta-information, other features such as rhythm, dynamics and harmony are crucial characteristics when comparing musical pieces . Music analysts and musicologists extract meaningful relationships from musical compositions regarding, for instance, style, epoch or composers . The results show that MusicVis supports music analysts in getting new insights about feature characteristics while increasing their engagement and willingness to explore. We conducted pair analytics sessions with 16 participants of different proficiency levels to gather qualitative feedback about the intuitiveness, traceability and understandability of our approach. Design-driven visual query filters enable analysts to investigate statistical and semantic patterns on various abstraction levels. We leverage glyph-based visualizations for harmony, rhythm and melody to demonstrate our technique's applicability. Gradual step-wise transitions empower analysts to retrace and comprehend the relationship between the CMN and abstract data representations. Our approach enhances the traditional analysis workflow by complementing CMN with interactive visualization entities as minimally intrusive augmentations. Therefore, music analysts often prefer to remain in their familiar context. Existing approaches use abstract data-driven visualizations to assist music analysis but lack a suitable connection to the CMN. Fully automated analysis instead misses human intuition about relevance. Music analysis tasks, such as structure identification and modulation detection, are tedious when performed manually due to the complexity of the common music notation (CMN).
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