Human performers introduce temporal variability in their performance of music. The variability consists of both long-range tempo changes and microtiming variability that are note-to-note level deviations from the nominal beat time. In many contexts, microtiming is important for achieving certain preferred characteristics in a performance, such as hang , drive, or groove ; but this variability is also, to some extent, stochastic. In this paper, we present a method for quantifying the microtiming variability. First, we transcribed drum performance audio files into empirical data using a very precise onset detection system. Second, we separated the microtiming variability into two components: systematic variability (SV), defined as recurrent temporal patterns, and residual variability (RV), defined as the residual, unexplained temporal deviation. The method was evaluated using computer-performed audio drum tracks and the results show a slight overestimation of the variability magnitude, but proportionally correct ratios between SV and RV. Thereafter two data sets were analyzed: drum performances from a MIDI drum kit and real-life drum performances from professional drum recordings. The results from these data sets show that up to 65 percent of the total micro-timing variability can be explained by recurring and consistent patterns.

Groove is a sensation of movement or wanting to move when we listen to certain types of music; it is central to the appreciation of many styles such as Jazz, Funk, Latin, and many more. To better understand the mechanisms that lead to the sensation of groove, we explore the relationship between groove and systematic microtiming deviations. Manifested as small, intentional deviations in timing, systematic microtiming is widely considered within the music community to be a critical component of music performances that groove. To investigate the effect of microtiming on the perception of groove we synthesized typical rhythm patterns for Jazz, Funk, and Samba with idiomatic microtiming deviation patterns for each style. The magnitude of the deviations was parametrically varied from nil to about double the natural level. In two experiments, untrained listeners and experts listened to all combinations of same and different music and microtiming style and magnitude combinations, and rated liking, groove, naturalness, and speed. Contrary to a common and frequently expressed belief in the literature, systematic microtiming led to decreased groove ratings, as well as liking and naturalness, with the exception of the simple short-long shuffle Jazz pattern. A comparison of the ratings between the two listener groups revealed this effect to be stronger for the expert listener group than for the untrained listeners, suggesting that musical expertise plays an important role in the perception and appreciation of microtiming in rhythmic patterns.

There is a quality of music that makes people tap their feet, rock their head, and get up and dance. The consistency of this experience among listeners was examined, in terms of differences in ratings across 64 music examples taken from commercially available recordings. Results show that ratings of groove, operationally defined as “wanting to move some part of the body in relation to some aspect of the sound pattern,” exhibited considerable interindividual consistency. Covariance patterns among the 14 rated words indicated four prominent factors, which could be labeled regular-irregular, groove, having swing, and flowing. Considering the wide range of music examples used, these factors are interpreted as reflecting psychological dimensions independent of musical genre and style.

Musicians and nonmusicians synchronized drum-beating movements to sound sequences composed of 90 successive interonset intervals that increased or decreased continually by various amounts of time. After the end of a sequence, they continued to produce 30 beats without interruption. Synchronization appeared both smooth and accurate for all levels of changing tempo. In general, actions preceded sounds with increasing intervals and lagged behind sounds with decreasing intervals, indicating that the stimulus change was not fully predicted. There was a tendency for the continuation intervals to change in the reverse direction of the preceding synchronization intervals, suggesting that the system retains information about the tempo change. We discuss these results in terms of the demands tempo change makes on timing mechanisms, and what they reveal about participants� ability to create and sustain an internal nonisochronous periodic process.

The purpose of this study was to explore whether listeners can use timing patterns to decode the intended emotional expression of musical performances. We gradually removed different acoustic cues (tempo, dynamics, timing, articulation) from piano performances rendered with various intended expressions (anger, sadness, happiness, fear) to see how such manipulations would affect a listener's ability to decode the emotional expression. The results show that (a) removing the timing patterns yielded a significant decrease in listeners' decoding accuracy, (b) timing patterns were by themselves capable of communicating some emotions with accuracy better than chance, and (c) timing patterns were less effective in communicating emotions than were tempo and dynamics. Implications for research on timing in performance are discussed.