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Quantitative analysis of commonalities and differences between recorded musicperformances is an increasingly common task in computational musicology. Atypical scenario involves manual annotation of different recordings of the samepiece along the time dimension, for comparative analysis of, e.g., the musicaltempo, or for mapping other performance-related information betweenperformances. This can be done by manually annotating one referenceperformance, and then automatically synchronizing other performances, usingaudio-to-audio alignment algorithms. In this paper we address several questionsrelated to those tasks. First, we analyze different annotations of the samemusical piece, quantifying timing deviations between the respective humanannotators. A statistical evaluation of the marker time stamps will provide (a)an estimate of the expected timing precision of human annotations and (b) aground truth for subsequent automatic alignment experiments. We then carry outa systematic evaluation of different audio features for audio-to-audioalignment, quantifying the degree of alignment accuracy that can be achieved,and relate this to the results from the annotation study.

A Study of Annotation and Alignment Accuracy for Performance Comparison in Complex Orchestral Music