  This paper proposes a methodology to map the various acoustic regimes of wind
instruments. The maps can be generated in a multi-dimensional space consisting
of design, control parameters, and initial conditions. The bound- aries of the
maps are obtained explicitly in terms of the parameters using a support vector
machine (SVM) classifier as well as a dedicated adaptive sam- pling scheme. The
approach is demonstrated on a simplified clarinet model for which several maps
are generated based on different criteria. Examples of computation of the
probability of occurrence of a specific acoustic regime are also provided. In
addition, the approach is demonstrated on a design optimization example for
optimal intonation.
