We are always looking for students to collaborate with, routinely supervising Master’s theses at the intersection of musicology and computing. We also offer for-credit semester projects and, occasionally, part-time employment opportunities in the shape of internships or assistantships.
- If you are inquiring about semester or thesis projects, please read the following list and contact either Dr. Yannis Rammos, or the designated project researcher, laying out your relevant background. You are also welcome to send us your own research proposal in a few sentences.
- If you are interested in a remunerated opportunity (internship or assistantship), please follow the instructions on this page (unless instructed otherwise in the project description).
Tradition and innovation in the notation of linear analyses
Master's thesis
“Linear” techniques of music analysis—such as those of Leo Mazel, Heinrich Schenker, Célestin Deliège, and several others—are a broad class of melodically oriented approaches with a common interest in “deep” (long-range) stepwise motions between tones. Linear analyses are typically expressed in extended score notations which challenge common practices of score reading, music typography, and symbolic encoding. The proposed Master’s project has a two-pronged goal: first, to develop software that renders MEI-encoded linear analyses as onscreen score notation, potentially building on the Verovio library; and second, to conceive, design, and implement radically new graphic notations of linear analyses, adapting ideas from network visualization or even digital cartography with minimal loss of expressive nuance.
The project should build on groundwork completed in our lab during the past three years: guidelines and a score interface for encoding linear analyses as annotated mathematical graphs; an MEI-based schema for embedding such encodings within symbolically encoded scores; and a corpus of canonical music analyses in this MEI format (soon to be published).
Prerequisites:
- strong interest in digital music typography or creative visualization;
- creative mindset, inclination for lateral thinking;
- speedy prototyping of visual concepts using D3.js or other SVG libraries;
- basic knowledge of Western tonal harmony and voice leading;
- graph theory fundamentals;
- strong academic writing skills; ability to distinguish between the purpose, functional logic, and workings of a system in coherent prose.
Indicative bibliography:
- Ericson, P., Rammos, Y., & Rohrmeier, M. (2023). A Generic Framework for Hierarchical Music Analysis. Music Encoding Conference Proceedings. https://doi.org/10.17613/bzaj-qq94
- Gould, E. (2011). Behind Bars: The Definitive Guide to Music Notation. Alfred Music.
- Schenker, H. (1969). Five Graphic Analyses. Dover. (Original work published 1932.)
Contact: Yannis Rammos
Curating the Leroy Ehrenreich Collection
Semester project
The Leroy Ehrenreich collection, privately held by the Academy of the Arts Bern, comprises thousands of hours of opera performances delivered by New York–based companies between the 1960s and 2000s. Many of these recordings are unofficial “bootlegs” furtively captured by Ehrenreich himself in the form of continuous, uncut audio. Unfortunately, the lack of timestamps, analytical annotations, and metadata for each opera section renders this valuable material unnavigable by scholars and students. The semester project aims at the development of techniques for: i) algorithmically segmenting each recorded opera into its constituent sections (“tracks”); ii) attaching relevant metadata to each section by recognizing its sonic signature and drawing information from semantic-web sources according to established music ontologies; iii) algorithmically identifying music-analytical features within the audio. The project is going to be undertaken in collaboration with the EPFL Cultural Heritage & Innovation Center.
Prerequisites:
- experience or strong interest in spectral analysis;
- experience or strong interest in music ontologies;
- Python fluency;
- knowledge of music theory rudiments.
Contact: Yannis Rammos