(Computing in Musicology 13) Published by CCARH and The MIT Press, 2004.
Modeling Rhythmic Motif Structure with Fuzzy Logic and Machine Learning
By Tillman Weyde
Research Unit for Music and Media Technology
Abstract: [ PDF ]
Analyzing the motif structure of rhythmic sequences is a central issue to music psychology, music theory, and computer applications in music. There are many approaches to the topic by music theorists, psychologists, and computer scientists, yet a model capable of integrating the different findings is still missing. The Integrated Segmentation and Similarity Model (ISSM) presented here is a newly developed model designed for this integration. It is based on a structural representation with detailed information on individual parts, a fuzzy system for rating structural alternatives, and algorithms for computationally efficient structure-recognition and system-optimization by machine learning. The design of the ISSM is described with a focus on musical motivation, and some results of the implementation and evaluation are discussed.