  Musicians produce individualized, expressive performances by manipulating
parameters such as dynamics, tempo and articulation. This manipulation of
expressive parameters is informed by elements of score information such as
pitch, meter, and tempo and dynamics markings (among others). In this paper we
present an interactive interface that gives users the opportunity to explore
the relationship between structural elements of a score and expressive
parameters. This interface draws on the basis function models, a data-driven
framework for expressive performance. In this framework, expressive parameters
are modeled as a function of score features, i.e., numerical encodings of
specific aspects of a musical score, using neural networks. With the proposed
interface, users are able to weight the contribution of individual score
features and understand how an expressive performance is constructed.
