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OFAI-TR-2002-13 ( 72kB g-zipped PostScript file,  96kB PDF file)

Quantifying the Differences between Music Performers: Score vs. Norm

Efstathios Stamatatos

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.

Keywords: Expressive music performance, Music performer recognition

Citation: Stamatatos E.: Quantifying the Differences between Music Performers: Score vs. Norm. Technical Report, Österreichisches Forschungsinstitut für Artificial Intelligence, Wien, TR-2002-13, 2002