Toward Understanding Expressive Percussion Through Content Based Analysis

Musical expression is the creative nuance through which a musician conveys emotion and connects with a listener. In un-pitched percussion instruments, these nuances are a very important component of performance. In this work, we present a system that seeks to classify different expressive articulation techniques independent of percussion instrument. One use of this system is to enhance the organization of large percussion sample libraries, which can be cumbersome and daunting to navigate. This work is also a necessary first step towards understanding musical expression as it relates to percussion performance. The ability to classify expressive techniques can lead to the development of models that learn the the functionality of articulations in patterns, as well as how certain performers use them to communicate their ideas and define their musical style. Additionally, in working towards understanding expressive percussion, we introduce a publicly available dataset of articulations recorded from a standard four piece drum kit that captures the instrument’s expressive range.