Download Synthesis by Mathematical Models Sound synthesis methods can be interpreted, from a mathe matical point of view, as a collection of techniques of selecting and conceptually organizing elements of a Hilbert space. In this sense, mathematics, being a highly structured and sophisticated system of classification, modeling and categorization, seems to be the natural tool to describe existing synthesis methods and to pro pose new ones. Because, from this perspective, one can think of any available (or theoretically predictable, or imaginable) synthe sis method as a collection of procedures to deal with meaningful parameters, with the term ”synthesis by mathematical models” we mean an extensive use of the modeling and categorization power of mathematics applied to the world of sounds. In this paper we give a few examples of sound synthesis tech niques, based on mathematical models. After reviewing shortly FM synthesis and synthesis by nonlinear distortion, and suggest ing some, to our advice, interesting open problems, we propose two different new methods: synthesis by means of elliptic func tions and synthesis by means of nowhere (or almostnowhere) dif ferentiable functions and lacunary series. The resulting waveforms have been produced using CSound as an audio engine, driven by Python scripts.
Download Hierarchical Organization and Visualization of Drum Sample Libraries Drum samples are an important ingredient for many styles of music. Large libraries of drum sounds are readily available. However, their value is limited by the ways in which users can explore them to retrieve sounds. Available organization schemes rely on cumbersome manual classification. In this paper, we present a new approach for automatically structuring and visualizing large sample libraries through audio signal analysis. In particular, we present a hierarchical user interface for efficient exploration and retrieval based on a computational model of similarity and self-organizing maps.