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dc.contributor.authorHolder, Ethan Grahamen_US
dc.date.accessioned2015-05-21T08:00:57Z
dc.date.available2015-05-21T08:00:57Z
dc.date.issued2015-05-20en_US
dc.identifier.othervt_gsexam:5322en_US
dc.identifier.urihttp://hdl.handle.net/10919/52376
dc.description.abstractIn the Western classical tradition, musicians play music from notated sheet music, called a score. When playing music from a score, a musician translates its visual symbols into sequences of instrument-specific physical motions. Hence, a music score's overall complexity represents a sum of the cognitive and mechanical acuity required for its performance. For a given instrument, different notes, intervals, articulations, dynamics, key signatures, and tempo represent dissimilar levels of difficulty, which vary depending on the performer's proficiency. Individual musicians embrace this tenet, but may disagree about the degrees of difficulty. This thesis introduces musiplectics (musiplectics = music + plectics, Greek for the study of complexity), a systematic and objective approach to computational assessment of the complexity of a music score for any instrument. Musiplectics defines computing paradigms for automatically and accurately calculating the complexity of playing a music score on a given instrument. The core concept codifies a two-phase process. First, music experts rank the relative difficulty of individual musical components (e.g., notes, intervals, dynamics, etc.) for different playing proficiencies and instruments. Second, a computing engine automatically applies this ranking to music scores and calculates their respective complexity. As a proof of concept of musiplectics, we present an automated, Web-based application called Musical Complexity Scoring (MCS) for music educators and performers. Musiplectics can engender the creation of practical computing tools for objective and expeditious assessment of a music score's suitability for the abilities of intended performers. This thesis is based on research submitted for publication at ONWARD'15.en_US
dc.format.mediumETDen_US
dc.publisherVirginia Techen_US
dc.rightsThis Item is protected by copyright and/or related rights. Some uses of this Item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).en_US
dc.subjectMusic Scoresen_US
dc.subjectMusic Complexity Assessmenten_US
dc.subjectNovel Computing Domainsen_US
dc.subjectMusicXMLen_US
dc.titleMusiplectics: Computational Assessment of the Complexity of Music Scoresen_US
dc.typeThesisen_US
dc.contributor.departmentComputer Scienceen_US
dc.description.degreeMSen_US
thesis.degree.nameMSen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineComputer Science and Applicationsen_US
dc.contributor.committeechairTilevich, Elien_US
dc.contributor.committeememberGillick, Amyen_US
dc.contributor.committeememberKnapp, Richard Benjaminen_US


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