Abstract
MUSIC OFTEN EVOKES A REGULAR BEAT AND A pleasurable sensation of wanting to move to that beat called groove. Recent studies show that a rhythmic pattern's ability to evoke groove increases at moderate levels of syncopation, essentially, when some notes occur earlier than expected. We present two studies that investigate that effect of syncopation in more realistic polyphonic music examples. First, listeners rated their urge to move to music excerpts transcribed from funk and rock songs, and to algorithmically transformed versions of these excerpts: 1) with the original syncopation removed, and 2) with various levels of pseudorandom syncopation introduced. While the original excerpts were rated higher than the de-syncopated, the algorithmic syncopation was not as successful in evoking groove. Consequently, a moderate level of syncopation increases groove, but only for certain syncopation patterns. The second study provides detailed comparisons of the original and transformed rhythmic structures that revealed key differences between them in: 1) the distribution of syncopation across instruments and metrical positions, 2) the counter-meter figures formed by the syncopating notes, and 3) the number of pickup notes. On this basis, we form four concrete hypotheses about the function of syncopation in groove, to be tested in future experiments.

Abstract

Abstract
Rhythmic similarity, a fundamental task within Music Information Retrieval, has recently been applied in creative music contexts to retrieve musical audio or guide audio-content transformations. However, there is still very little knowledge of the typical rhythmic similarity values between overlapping musical structures per instrument, genre, and time scales, which we denote as rhythmic compatibility. This research provides the first steps towards the understanding of rhythmic compatibility from the systematic analysis of MedleyDB, a large multi-track musical database composed and performed by artists. We apply computational methods to compare database stems using representative rhythmic similarity metrics - Rhythmic Histogram (RH) and Beat Spectrum (BS) - per genre and instrumental families and to understand whether RH and BS are prone to discriminate genres at different time scales. Our results suggest that 1) rhythmic compatibility values lie between [.002,.354] (RH) and [.1,.881] (BS), 2) RH outperforms BS in discriminating genres, and 3) different time scale in RH and BS impose significant differences in rhythmic compatibility. © 2021 ACM.

Abstract

Abstract
In this paper we present a 12-dimensional tonal space in the context of the Tonnetz, Chew's Spiral Array, and Harte's 6-dimensional Tonal Centroid Space. The proposed Tonal Interval Space is calculated as the weighted Discrete Fourier Transform of normalized 12-element chroma vectors, which we represent as six circles covering the set of all possible pitch intervals in the chroma space. By weighting the contribution of each circle (and hence pitch interval) independently, we can create a space in which angular and Euclidean distances among pitches, chords, and regions concur with music theory principles. Furthermore, the Euclidean distance of pitch configurations from the centre of the space acts as an indicator of consonance.