Abstract

Inter-performer deviations in pitch, timing, dynamics, and timbre can be used to model individuals’ music performance style provided that there is sufficient intra-performer similarity. If a performer’s variability in performance parameters exceeds the variability across performers it is hard to create a discriminative model between performers that can predict performer identity. This paper investigates the intra- and inter-performer consistency in singers trained in the western art music tradition using a range of pitch, timing, dynamics, and timbre descriptors. Specifically, it examines the utility of these descriptors in a singer-identity task completed both computationally by a support vector machine classifier and by human listeners and considers the broader implications for intra- and inter-performance similarity and variability in music performance modelling.

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