A Model Comparison for Chord Prediction on the Annotated Beethoven Corpus


This paper models predictive processing of chords using a corpus of Ludwig van Beethoven’s string quartets. A recently published dataset consisting of expert harmonic analyses of all Beethoven string quartets was used to evaluate an $n$-gram language model as well as a recurrent neural network (RNN) architecture based on long-short-term memory (LSTM). We compare model performances over different periods of Beethoven’s creative activity and provide a baseline for future research on predictive processing of chords in full Roman numeral representation on this dataset

Proceedings of the 16th Sound & Music Computing Conference (SMC 2019)
Fabian C. Moss
Fabian C. Moss
Assistant Professor for Digital Music Philology and Music Theory

Fabian C. Moss is an assistant professor for Digital Music Philology and Music Theory at Julius-Maximilians University Würzburg (JMU), Germany.