Classification in music: a computational model for paradigmatic analysis
Christina Anagnostopoulou, Gert Westermann · 1997
We present a computational model for the paradigmatic analysis of musical pieces, which is the classification of musical segments into similarity-based categories. The model requires the analyst to make explicit choices for the characteristics by which the musical segments are described. The classification of the segments into categories is determined by these characteristics and is performed by a self-organizing neural network algorithm. In this way, traditional problems associated with paradigmatic analysis, namely lack of consistency and objectivity, can be avoided. Moreover, the model extends the analytical technique by providing different levels of classification, prototypes for each class, and by showing relations between classes. 1 Introduction The paradigmatic analysis (henceforth PA) of musical pieces has long been criticized for its reliance on intuition and the resulting inconsistencies [1]. In this paper, we describe a formal model for this task as a way to address such cr...