- Understanding and analyzing features of large music score corpora is a complex problem and provides numerous research opportunities within a growing community
- Detecting similarities and differences of a large score set is an interesting task for domain experts
- Manually investigating and extracting information and features from music scores is tedious and time-consuming
- The objective is to develop an interactive visual music score corpora explorer which supports users in getting an overview a large music score dataset available in MusicXML
- Implementation of user-steered analysis methods based on new visualizations to identify musical patterns of and between different low- and high-level features
- How can we visualize relevant information of large music score collections?
- How can musical features be visually encoded effectively?
- What features are interesting for music analysts and how to support effective user interaction?
- Automatically extracting semantic information that is relevant to analysts is difficult or even impossible.
- Perform a literature research to identify gaps of state-of-the-art visualization solution that support music score collection analysis (recommended: within the accompanying seminar)
- Examine and identify existing approaches and analysis models
- Work with a large dataset of music scores based on the established MusicXML standard format using the Python Library music21
- Implement a visualization pipeline that processes and transforms raw MusicXML files into interactive visualization models supporting user-steered analysis
- Help analysts to focus on features of interest ranging from meta-features (e.g., composer, epoch, genre) to low-level features (e.g., dynamics, articulation, instructions, tonality)
- Deep Interest in learning about music, its features, and state-of-the-art formats
- Basic knowledge about information visualization (e.g., Visual Variables, Gestalt Laws, Visual Information-Seeking Mantra, Linking & Brushing, etc.)
- Readiness to do creative research work independently
- Basic knowledge of Git (Issues, Feature Branches, Documentation, etc.)
- Scope: Bachelor / Master
- Project/Thesis Duration: 3 months / 3 months (Bachelor), 3 months / 6 months (Master)
- Start: immediately
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