Technical Reports - Query Results
Your query term was 'number = 2001-32'1 report found
- ÖFAI-TR-2001-32 (
161kB g-zipped PostScript file, 
626kB PDF file)Machine Discoveries: A Few Simple, Robust Local Expression Principles
- Gerhard Widmer
- The paper presents a new approach to discovering general rules of
expressive music performance from real performance data via inductive
machine learning. A new learning algorithm is briefly presented,
and then an experiment with a very large data set
(performances of 13 Mozart piano sonatas) is described.
The new learning algorithm succeeds in discovering some extremely
simple and general principles of musical performance (at the level
of individual notes), in the form of categorical prediction rules.
These rules turn out to be very robust and general: when tested on
performances by a different pianist and even on music of a different
style (Chopin), they exhibit a surprisingly high degree of
predictive accuracy.
Keywords: Expressive Music Performance, Machine Learning, Knowledge Discovery,
- The paper presents a new approach to discovering general rules of
expressive music performance from real performance data via inductive
machine learning. A new learning algorithm is briefly presented,
and then an experiment with a very large data set
(performances of 13 Mozart piano sonatas) is described.
The new learning algorithm succeeds in discovering some extremely
simple and general principles of musical performance (at the level
of individual notes), in the form of categorical prediction rules.
These rules turn out to be very robust and general: when tested on
performances by a different pianist and even on music of a different
style (Chopin), they exhibit a surprisingly high degree of
predictive accuracy.