Integrating Segmentation and Similarity in Melodic Analysis
Tillman Weyde · City Research Online (City University London) · 2002
The recognition of melodic structure depends on both the segmen-tation into structural units, the melodic motifs, and relations of motifs which are mainly determined by similarity. Existing mod-els and studies of segmentation and motivic similarity cover only certain aspects and do not provide a comprehensive or coherent theory. In this paper an Integrated Segmentation and Similarity Model (ISSM) for melodic analysis is introduced. The ISSM yields an interpretation similar to a paradigmatic analysis for a given melody. An interpretation comprises a segmentation, assignments of related motifs and notes, and detailed information on the differ-ences of assigned motifs and notes. The ISSM is based on gener-ating and rating interpretations to find the most adequate one. For this rating a neuro-fuzzy-system is used, which combines knowl-edge with learning from data. The ISSM is an extension of a system for rhythm analysis. This paper covers the model structure and the features relevant for melodic and motivic analysis. Melodic segmentation and sim-ilarity ratings are described and results of a small experiment which show that the ISSM can learn structural interpretations from data and that integrating similarity improves segmentation performance of the model. 1.