SCHUBOT

Combines various methods for automated musical analysis, applying machine learning techniques to gain insight about the Lieder of composer Franz Schubert. The algorithms presented in this paper analyze the harmonies, melodies, and texts of these songs. The paper begins with an exploration of the relevant music theory and machine learning algorithms and a discussion of Schubert's place in the world of music theory. The paper then focuses on automated harmonic analysis and hierarchical decomposition of MusicXML data, followed by melodic analysis using unsupervised clustering methods. The paper then analyzes the song texts in context of the relevant musical features, combining natural language processing with feature extraction to pinpoint trends in Schubert's career.