This thesis describes a system that incorporates techniques developed by musicologists to do stylistic analysis of music, an important applied field in music theory analysis. To do the analysis requires the knowledge of many musicological analysis methods and pattern recognition algorithms that are central issues to this project. In addition, AI techniques of learning were used to improve the whole system's skills. The conclusions reached as a result of this project were that computers can perform musical tasks usually associated exclusively with naturally intelligent musicologists, and that learning techniques can expand and enrich the behavior of musically intelligent systems.
Library of Congress Subject Headings
Musical analysis--Data processing; Sonatas (Piano)--Data processing; Music--Computer programs
Computer Science (MS)
Department, Program, or Center
Computer Science (GCCIS)
Lin-Jeng, Emily Feng-Hwa, "Stylistic analysis and recognition of piano sonatas of four composers -- Mozart, Chopin, Debussy, Anton Webern" (1987). Thesis. Rochester Institute of Technology. Accessed from
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