Analysis and Prediction of Piano Performances
Using Inductive Logic Programming

Erika Van Baelen and Luc De Raedt

Department of Computer Science, Katholieke Universiteit Leuven
Celestijnenlaan 200A, B-3001 Heverlee, Belgium
Email: Luc.DeRaedt@cs.kuleuven.ac.be


Abstract. Starting from the work of Matthew Dovey on analysing Rachmarinoffs 
piano performances using inductive logic programming, we
show how to apply the clausal discovery engine Claudien to induce theodes 
for predicting MIDI files from the musical analysis of a score.
This extends Doveys work in several directions: MIDI-encodings are used
instead of the older Ampico, a richer musical analysis within LaRues
SHMRG-model is applied, a much finer qualitative analysis of features
is learned (making it nearly quantitative), and predictions are made.
The application is not only relevant as yet another inductive logic programming 
benchmark, but also as a demonstration of the need for multiple 
predicate learning, sequence prediction and number handling in
inductive logic programming. Furthermore, the results presented here
can be considered the first original application of the clausal discovery
engine Claudien.
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