| Abstract: | This. paper addresses the problem of identifying the
most likely music performer, given a set of performances of the
same piece by a number of skilled candidate pianists. We propose a
set of features for representing the stylistic characteristics of a
music performer. A database of piano performances of 22 pianists
playing two pieces by F. Chopin is used in the presented
experiments. Due to the limitations of the training set size and the
characteristics of the input features we propose an ensemble of
simple classifiers derived by both subsampling the training set and
subsampling the input features. Preliminary experiments show that
the resulting ensemble is able to efficiently cope with this difficult
musical task, displaying a level of accuracy unlikely to be matched
by human listeners (under similar conditions). |
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