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. / Master of Science

The original aim of the research was to investigate the conceptual dimensions of style in tonal music in order to provide grounds for an objective, measurable categorization of the phenomenon that could be construed as the basis of a scientific taxonomy of musical styles. However, this is a formidable task that surpasses the practical possibilities of the project, which would hence concentrate on creating the tools that would be needed for the following stage. A review of previous attempts to deal with style in music provided a number of guidelines for the process of dealing with the material. The project intends to avoid the subjectivity of musical analysis concentrating on music observable features. A database of 250 keyboard scores in MusicXML format was built to the purpose of covering the whole span of styles in tonal music, from which it should be possible to extract features to be used in style categorization. Early on, it became apparent that most meaningful pitch-related features are linked to scale degrees, thus essentially depending on functional labeling, requiring the knowledge of the key of the music as a point function. Different proposed alternatives to determine the key were considered and a method decided upon. Software was written and its effectiveness tested. The method proved successful in determining the instant key with as much precision as feasible. On this basis, it became possible to functionally label scale degrees and chords. This software constitutes the basic tool for the extraction of pitch-related features. As its first use, the software was applied to the score database in order to quantify the usage of scale degrees and chords. The results indisputably showed that tonal music can be characterized by specific proportions in the use of the different scale degrees, whereas the use of chords shows a constant increase in chromaticism. Part of the material of this work appeared in the Springer-Verlag's 2006 volume of Lecture Notes in Computer Science.

The diploma thesis specifies digital methods of optical recognition of a notation, by detailed analysis of methods based on removal of notation lines and creation of a test program which automatically converts the images written in the notation into digital format. This work summarizes the knowledge from the research and practical part. In the research section, key chapters are described as OMR architecture, including processing, symbol classification, postprocessing, and more. The practical part of the thesis presents the results of the development and testing of the proposed application.

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The Master's Thesis discusses the possibilities of automatic melody harmonization. System use dictionary method for harmonization, this was inspired with comprimation algorithm LZW. System's output file is in MusicXML format.