| Abstract: | In this study, a comparison of features for
discriminating between different music performers
playing the same piece is presented. Based on a series
of statistical experiments on a data set of piano pieces
played by 22 performers, it is shown that the
deviation from the performance norm (average
performance) is better able to reveal the performers’
individualities in comparison to the deviation from
the printed score. In the framework of automatic
music performer recognition, the norm-based features
prove to be very accurate in intra-piece tests (training
and test set taken from the same piece) and very
stable in inter-piece tests (training and test sets taken
from different pieces). Moreover, it is empirically
demonstrated that the average performance is at least
as effective as the best of the constituent individual
performances while ‘extreme’ performances have the
lowest discriminatory potential when used as norm. |
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Greek