  Musical rhythms performed by humans typically show temporal fluctuations.
While they have been characterized in simple rhythmic tasks, it is an open
question what is the nature of temporal fluctuations, when several musicians
perform music jointly in all its natural complexity. To study such fluctuations
in over 100 original jazz and rock/pop recordings played with and without
metronome we developed a semi-automated workflow allowing the extraction of
cymbal beat onsets with millisecond precision. Analyzing the inter-beat
interval (IBI) time series revealed evidence for two long-range correlated
processes characterized by power laws in the IBI power spectral densities. One
process dominates on short timescales ($t < 8$ beats) and reflects microtiming
variability in the generation of single beats. The other dominates on longer
timescales and reflects slow tempo variations. Whereas the latter did not show
differences between musical genres (jazz vs. rock/pop), the process on short
timescales showed higher variability for jazz recordings, indicating that jazz
makes stronger use of microtiming fluctuations within a measure than rock/pop.
Our results elucidate principles of rhythmic performance and can inspire
algorithms for artificial music generation. By studying microtiming
fluctuations in original music recordings, we bridge the gap between
minimalistic tapping paradigms and expressive rhythmic performances.
