This paper describes a computational model of loudness variations in expressive ensemble performance. The model predicts and explains the continuous variation of loudness as a function of information extracted automatically from the written score. Although such models have been proposed for expressive performance in solo instruments, this is (to the best of our knowledge) the first attempt to define a model for expressive performance in ensembles. To that end, we extend an existing model that was designed to model expressive piano performances, and describe the additional steps necessary for the model to deal with scores of arbitrary instrumentation, including orchestral scores. We test both linear and non-linear variants of the extended model n a data set of audio recordings of symphonic music, in a leave-one-out setting. The experiments reveal that the most successful model variant is a recurrent, non-linear model. Even if the accuracy of the predicted loudness varies from one recording to another, in several cases the model explains well over 50 of the variance in loudness.
@cite_13: The KTH rule system models performance principles used by musicians when performing a musical score, within the realm of Western classical, jazz and popular music. An overview is given of the major rules involving phrasing, micro-level timing, metrical patterns and grooves, articulation, tonal tension, intonation, ensemble timing, and performance noise. By using selections of rules and rule quantities, semantic descriptions such as emotional expressions can be modeled. A recent real-time implementation provides the means for controlling the expressive character of the music. The communicative purpose and meaning of the resulting performance variations are discussed as well as limitations and future improvements.
One of the most well-known rule-based systems for musical music performance was developed at the Royal Institute of Technology in Stockholm (referred to as the KTH model) @cite_13 . This system is top-down approach that describes expressive performances using a set of (music theoretically sound cognitively plausible) performance rules that predict aspects of timing, dynamics and articulation, based on a local musical context.