Beyond MIDI: The Handbook of Musical Codes

Selfridge-Field, Eleanor

doi:10.2307/900186

Cited by 38 publications

(4 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, constraining patterns to remain within a single voice is crucial. This pattern identification is typically an insitu annotation using the Common Music Notation [65] which is the representation analysts are most familiar with. R2: Detect melodic pattern reoccurrences across the piece in different voices -Identifying reoccurrences and variations of a theme typically requires analyzing multiple voices separately to determine how a composer develops a melodic topic during a composition.…”

Section: Analysis Tasks and Requirementsmentioning

confidence: 99%

See 1 more Smart Citation

Augmenting Digital Sheet Music through Visual Analytics

Miller

Fürst

Schäfer

et al. 2022

Computer Graphics Forum

View full text Add to dashboard Cite

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). Fully automated analysis instead misses human intuition about relevance. Existing approaches use abstract data‐driven visualizations to assist music analysis but lack a suitable connection to the CMN. Therefore, music analysts often prefer to remain in their familiar context. Our approach enhances the traditional analysis workflow by complementing CMN with interactive visualization entities as minimally intrusive augmentations. Gradual step‐wise transitions empower analysts to retrace and comprehend the relationship between the CMN and abstract data representations. We leverage glyph‐based visualizations for harmony, rhythm and melody to demonstrate our technique's applicability. Design‐driven visual query filters enable analysts to investigate statistical and semantic patterns on various abstraction levels. 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. The results show that MusicVis supports music analysts in getting new insights about feature characteristics while increasing their engagement and willingness to explore.

show abstract

Section: Analysis Tasks and Requirementsmentioning

confidence: 99%

“…Well-known is the wenzi pu (文字譜) notation for the guqin instrument, common in seventh-century China. More common to many today is the Western Common Music Notation [65].…”

Section: Introductionmentioning

confidence: 99%

Augmenting Digital Sheet Music through Visual Analytics

Miller

Fürst

Schäfer

et al. 2022

Computer Graphics Forum

View full text Add to dashboard Cite

show abstract

“…Surprisingly, it is also the most limited in terms of the number of aspects of music that it can represent (Fujishima, 1999), since it is designed to be read by hardware, and therefore consists of hardware protocols and instructions, rather than a more "musical" representation. Deeper exploration of different MRLs, their thorough analyses and reviews can be found in (McLane, 1996;Repetto & Selfridge-Field, 1997;Selfridge-Field, 1994). Since symbolic representations already contain many low-level features explicitly, inferring high-level features is less complex, bypassing signal processing altogether.…”

Section: Symbolic Representationsmentioning

confidence: 99%

High-Level Musical Content-Based Music Information Retrieval: A State-of-the-Art Review

Gedizlioglu¹,

Erol²

2020

JSTR

View full text Add to dashboard Cite

Music Information Retrieval (MIR) is an interdisciplinary field that involves automating music processing for the purpose of accessing and managing large music collections. Motivated by the rapid growth of digital music content, it encompasses a broad set of strategies from diverse disciplines. In this paper, we provide a task-centric perspective of this field with particular emphasis on high-level content analysis. We provide a general context to explain the contributions from various disciplines for those wishing to learn about this field. We also discuss challenges and future directions to stimulate further research.

show abstract

“…Many researchers have addressed the notation-modeling problem with its related rendering through computer systems. [4][5][6][7][8][9]…”

Section: Symbolic Music Representation In Mpegmentioning

confidence: 99%