Hierarchical and reductive analyses are ubiquitous in music theory and important to a growing range of related disciplines. Unfortunately, corpora of symbolically encoded hierarchical analyses are scant at best, while no software has been available to facilitate corpus development. In response, we are actively prototyping a versatile tool for the encoding of hierarchical analyses as annotations to scores in the Music Encoding Initiative format. Our web app is being developed in tandem with a corpus of primarily Schenkerian analyses; some GTTM prolongational reductions and Maximal Outerplanar Graphs are also included in the corpus as proofs of concept. Likewise in progress is a comprehensive set of encoding conventions for the consistent symbolic encoding of Schenkerian analyses without loss of semantic nuance.
Analytical relations are stored within the score file as MEI metadata in adherence to a scheme proposed by Rizo and Marsden. We rely on the rendering engine Verovio for rendering the MEI XML score, and on our own algorithms for drawing analytical overlays on it. The app provides a suite of features for manipulating all graphic elements of the analysis and relevant parts of the original score notation. We hope and expect that the app will be of value to researchers, practitioners, and music pedagogues alike.
Publications are in progress. Meanwhile, an extended abstract is available for the following poster:
- Ericson P, Rohrmeier, M (2020) Hierarchical Annotation of MEI-Encoded Sheet Music. Presented as Late-Breaking Poster at the International Society for Music Information Retrieval (ISMIR) conference, Montréal, Canada.
You find the app here:
https://dcmlab.github.io/reductive_analysis_app/index.html
(this is still a prototype)