Abstract
Sebastian Flossmann
One of the crucial points in empirical performance analysis is the acquisition of data. Automatically extracting information related to timing, dynamics and articulation from audio recordings is still not possible at the level of precision required for large-scale music performance studies. The Bösendorfer computer-controlled grand piano makes it possible to record performance data in the symbolic domain instead of the audio domain, providing very precise data. This work is part of a series of music performance studies centered on the Magaloff Corpus, a unique resource of performances recorded on such an instrument. The collection comprises Chopin's complete works for solo piano performed by Nikita Magaloff in six public appearances in spring 1989 at the Vienna Konzerthaus.
The present study focuses on the phenomenon of performance errors. We examine the errors Magaloff makes from different angles. First, we give an overview of the number of errors in the data and relate them to the tempo of the performances. Second, we investigate perceptual aspects of the errors: how well do they fit into the surrounding harmonic context, how loud are they played in comparison to other notes in the vicinity, and where are they located in terms of voice. Third, we examine two error patterns more closely that reoccur throughout the corpus: the omission of inner voices and inserted notes in sequences of parallel octaves.