Abstract

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

Publication Date

3-26-1987

Document Type

Thesis

Student Type

Graduate

Degree Name

Computer Science (MS)

Department, Program, or Center

Computer Science (GCCIS)

Advisor

John Biles

Advisor/Committee Member

Stanislaw Radziszowski

Advisor/Committee Member

Peter Anderson

Comments

Physical copy available from RIT's Wallace Library at MT6.L56S89 1987

Campus

RIT – Main Campus

Download

Share

COinS