Musiplectics: Computational Assessment of the Complexity of Music Scores

In 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." A 'pause' is a pleasant interruption along a path; followed by an architectural invitation to stop, explore, stand, lean, sit or lay down. A successful place of 'pause' stimulates the senses and possibly alters the mood of the visitors.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Computer Science and Applications

Department dc:contributor.department

Computer Science

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2015

Author dc:creator

• Holder, Ethan Graham

Chair dc:contributor.committeechair

• Tilevich, Eli

Committee members dc:contributor.committeemember

• Gillick, Amy
• Knapp, R. Benjamin

• Music Scores
• Music Complexity Assessment
• Novel Computing Domains
• MusicXML

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Dc Identifier Other

vt_gsexam:5322

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/52376