- Analyzing melodic patterns or themes in music is a common musicological task
- The automatic idenitification of melody information is a challenge that can benefit from interactive visualization
- Your target in this project is to develop/extend an interactive visual analysis prototype that supports the visual analysis melodic patterns based on music data that is available in the MusicXML format.
- There are numerous style means such as repetition, inversion, and transposition that are relevant to musicologists when analyzing melodic features due to the impact on the listener.
- How can we use interactive visual methods to identify specific melodic patterns?
- What aspects are important when implementing an analysis prototype that supports the visual analysis and identification of melodic patterns?
- Implement given melodic operators that can be applied to a one-dimensional melodic search pattern such as inversion, repetition, transposition, augmentation, diminuition
- Identify recurring patterns within single musical pieces and extend this approach to a collection of selected musical pieces (dataset will be provided)
- Implement user interaction techniques that enable music analysts to apply the melodic operators mentioned above
- Create a visualization that provides an overview of the results of user inquiries or identify frequent melodic patterns.
- Interest in learning about music data (e.g., notes, pitches, rhythm).
- Basic knowledge about information visualization and data mining.
- Readiness to do creative research work independently
Scope / Duration / Start
- Scope: Bachelor / Master
- Project/Thesis Duration: 3 months / 3 months (Bachelor), 3 months / 6 months (Master)
- Start: Consider the project registration deadlines provided by the Department of Computer and Information Science (BA | MA)
- M. Good. MusicXML for notation and analysis. The virtual score: representation, retrieval, restoration 12:113-124, 2001. https://www.musicxml.com/de/
- Cuthbert, M. S., & Ariza, C. music21: A toolkit for computer-aided musicology and symbolic music data. (2010). https://web.mit.edu/music21/
- Mikael Laurson, Mika Kuuskankare, Vesa Norilo: An Overview of PWGL, a Visual Programming Environment for Music. Comput. Music. J. 33(1): 19-31 (2009)
- Jan Koláček. Global Chant Database. http://www.globalchant.org/search.php. (2009)
- Irwin, K. Musipedia: The open music encyclopedia. Reference Reviews. (2008): https://www.musipedia.org/
- Kelkar, T., & Jensenius, A. R. Exploring melody and motion features in “sound-tracings”. In Proceedings of the SMC Conferences (pp. 98-103). Aalto University. (2017).