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Musical expertise improves the precision of timing perception and performance – but is this expertise generic, or is it tied to the specific style(s) and genre(s) of one’s musical training? We asked expert musicians from three musical genres (folk, jazz, and EDM/hip-hop) to align click tracks and tap in synchrony with genre-specific and genre-neutral sound stimuli to determine the perceptual center (“P-center”) and variability (“beat bin”) for each group of experts. We had three stimulus categories – Organic, Electronic, and Neutral sounds – each of which had a 2 × 2 design of the acoustic factors Attack (fast/slow) and Duration (short/long). We found significant effects of Genre expertise, and a significant interaction for both P-center and P-center variability: folk and jazz musicians synchronize to sounds typical of folk and jazz in a different manner than the EDM/hip-hop producers. The results show that expertise in a specific musical genre affects our low-level perceptions of sounds as well as their affordance(s) for joint action/synchronization. The study provides new insights into the effects of active long-term musical enculturation and skill acquisition on basic sensorimotor synchronization and timing perception, shedding light on the important question of how nature and nurture intersect in the development of our perceptual systems.

In speech and music, the acoustic and perceptual onset(s) of a sound are usually not congruent with its perceived temporal location. Rather, these "P-centers" are heard some milliseconds after the acoustic onset, and a variety of techniques have been used in speech and music research to find them. Here we report on a comparative study that uses various forms of the method of adjustment (aligning a click or filtered noise in-phase or anti-phase to a repeated target sound), as well as tapping in synchrony with a repeated target sound. The advantages and disadvantages of each method and probe type are discussed, and then all methods are tested using a set of musical instrument sounds that systematically vary in terms of onset/rise time (fast vs. slow), duration (short vs. long), and center frequency (high vs. low). For each method, the dependent variables were (a) the mean P-center location found for each stimulus type, and (b) the variability of the mean P-center location found for each stimulus type. Interactions between methods and stimulus categories were also assessed. We show that (a) in-phase and anti-phase methods of adjustment produce nearly identical results, (b) tapping vs. click alignment can provide different yet useful information regarding P-center locations, (c) the method of adjustment is sensitive to different sounds in terms of variability while tapping is not, and (d) using filtered noise as an alignment probe yields consistently earlier probe-onset locations in comparison to using a click as a probe. peerReviewed

The perceptual center (P-center) of a sound is typically understood as the specific moment at which it is perceived to occur. Using matched sets of real and artificial musical sounds as stimuli, we probed the influence of attack (rise time), duration, and frequency (center frequency) on perceived P-center location and P-center variability. Two different methods to determine the P-centers were used: Clicks aligned in-phase with the target sounds via the method of adjustment, and tapping in synchrony with the target sounds. Attack and duration were the primary cues for P-center location and P-center variability; P-center variability was found to be a useful measure of P-center shape. Consistent interactions between attack and duration were also found. Probability density distributions for each stimulus display a systematic pattern of P-center shapes ranging from narrow peaks close to the onset of sounds with fast attack and short duration, to wider and flatter shapes indicating a range synchronization points for sounds with slow attack and long duration. The results support the conception of P-centers as not simple time points, but "beat bins" with characteristic shapes, and the shapes and locations of these beat bins are dependent upon both the stimulus and the synchronization task. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Links between music and body motion can be studied through experiments called sound-tracing. One of the main challenges in such research is to develop robust analysis techniques that are able to deal with the multidimensional data that musical sound and body motion present. The article evaluates four different analysis methods applied to an experiment in which participants moved their hands following perceptual features of short sound objects. Motion capture data has been analyzed and correlated with a set of quantitative sound features using four different methods: (a) a pattern recognition classifier, (b) t-tests, (c) Spearman s Á correlation, and (d) canonical correlation. This article shows how the analysis methods complement each other, and that applying several analysis techniques to the same data set can broaden the knowledge gained from the experiment. Copyright ACM, 2013. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The de nitive version was published in ACM Transactions on Applied Perception 10(2).

The paper presents the interactive music system SoloJam, which allows a group of participants with little or no musical training to effectively play together in a "band-like" setting. It allows the participants to take turns playing solos made up of rhythmic pattern sequences. We specify the issue at hand for enabling such participation as being the requirement of decentralised coherent circulation of playing solos. Satisfying this requirement necessitates some form of intelligence within the devices used for participation, with each participant being associated with their respective enabling device. Markets consist of buyers and sellers, which interact with each other in order to trade commodities. Based on this idea, we let devices enable buying and selling, more precisely bidding and auctioneering, and assist participants trade in musical terms. Consequentially, the intelligence in the devices is modelled as their ability to help participants trade solo playing responsibilities with each other. This requires them to possess the capability of assessing the utility of the associated participant's deservedness of being the soloist, the capability of holding auctions on behalf of the participant, and of enabling the participant bid within these auctions. We show that holding auctions and helping bid within them enables decentralisation of co-ordinating solo circulation, and a properly designed utility function enables coherence in the musical output. The market-based approach helps achieve decentralised coherent circulation with artificial agents simulating human participants. The effectiveness of the approach is further supported when human users participate. As a result, the approach is shown to be effective at enabling participants with little or no musical training to play together in SoloJam.

In our own and other research on music-related actions, findings suggest that perceived action and sound are broken down into a series of chunks in people's minds when they perceive or imagine music. Chunks are here understood as holistically conceived and perceived fragments of action and sound, typically with durations in the 0.5 to 5 seconds range. There is also evidence suggesting the occurrence of coarticulation within these chunks, meaning the fusion of small-scale actions and sounds into more superordinate actions and sounds. Various aspects of chunking and coarticulation are discussed in view of their role in the production and perception of music, and it is suggested that coarticulation is an integral element of music and should be more extensively explored in the future.

From our studies of sound‐related movement (http://musicalgestures.uio.no), we have reason to believe that both sound‐producing and sound‐accompanying movements are centered around what we call goal‐points, meaning certain salient events in the music such as downbeats, or various accent types, or melodic peaks. In music performance, these goal‐points are reflected in the positions and shapes of the performers' effectors (fingers, hands, arms, torso, etc.) at certain moments in time, similar to what is known as keyframes in animation. The movement trajectories between these goal‐points, similar to what is known as interframes in animation, may often demonstrate the phenomenon of coarticulation, i.e. that the various smaller movement are subsumed under more superordinate and goal‐directed movement trajectories. In this paper, we shall present a summary of recent human movement research in support of this scheme of goal‐points and coarticulations, as well as demonstrate this scheme with data from our ongoing motion capture studies of pianists' performance and other researchers' motion capture data.