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