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The COVID-19 pandemic has brought unprecedented challenges to the maritime supply chain and called for accelerated adoption of digital technologies in various aspects of maritime operations, including the area of maritime education and training (MET). This paper aims to discuss the current maritime simulator-based training and educational practices that forms an integral part in seafarer training and competency development. The study provides a review of the existing simulators in use in MET, and discusses upon the technological and pedagogical advancement of maritime simulator-based training interventions with predictions regarding the future MET practices with use of virtual reality and cloud-based simulators. This study—by focusing on ship’s bridge operations—highlights the characteristics of various types of simulators and also discusses the role of instructors, challenges, and opportunities involving future simulator-based MET due to accelerated adoption of digital technologies and the need to comply with pandemic-related restrictions for MET institutes. The analysis generated in the paper may contribute to the ongoing discussion regarding the future of simulator-based MET and the fulfillment of the UN Sustainable Development Goal (SDG) 4 in the maritime sector.

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

This article addresses the computational estimation of attack regions in audio recordings. Previous attempts to do so were based on the reduction of the audio waveform into an envelope curve, which decreases its temporal resolution. The proposed approach detects the attack region directly from the audio waveform. The attack region is modeled as a line starting from a low-amplitude point and intersecting one of the local maxima according to two principles: (1) maximizing the slope, while favoring, at the same time, a higher peak if the slope remains only slightly lower and (2) dismissing initial attack regions of relatively low amplitude. The attack start position is fine-tuned by intersecting the attack slope with the audio waveform. The proposed method precisely pinpoints the attack region in cases where it is unambiguously observable from the waveform itself. In such cases, previous methods selected a broader attack region due to the loss of temporal resolution. When attack regions are less evident, the proposed method's estimation remains within the range of results provided by other methods. Applied to the prediction of judgments of P-center localization [Danielsen, Nymoen, Anderson, Câmara, Langerod, Thompson, and London, J. Exp. Psychol. Hum. Percept. Perform. 45, 402-418 (2019)], the proposed method shows a significant increase in precision, at the expense of recall.

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).

This paper reports on two experiments that investigated the expressive means through which musicians well versed in groove-based music signal the intended timing of a rhythmic event. Data were collected from 21 expert electric guitarists and 21 bassists, who were instructed to perform a simple rhythmic pattern in three different timing styles—“laid-back,” “on-the-beat,” and “pushed”—in tandem with a metronome. As expected, onset and peak timing locations corresponded to the instructed timing styles for both instruments. Regarding sound, results for guitarists revealed systematic differences across participants in the duration and brightness [spectral centroid (SC)] of the guitar strokes played using these different timing styles. In general, laid-back strokes were played with a longer duration and a lower SC relative to on-the-beat and pushed strokes. Results for the bassists indicated systematic differences in intensity (sound-pressure level): pushed strokes were played with higher intensity than on-the-beat and laid-back strokes. These results lend further credence to the hypothesis that both temporal and sound-related features are important indications of the intended timing of a rhythmic event, and together these features offer deeper insight into the ways in which musicians communicate at the microrhythmic level in groove-based music.

This study reports on an experiment that tested whether drummers systematically manipulated not only onset but also duration and/or intensity of strokes in order to achieve different timing styles. Twenty-two professional drummers performed two patterns (a simple “back-beat” and a complex variation) on a drum kit (hi-hat, snare, kick) in three different timing styles (laid-back, pushed, on-beat), in tandem with two timing references (metronome and instrumental backing track). As expected, onset location corresponded to the instructed timing styles for all instruments. The instrumental reference led to more pronounced timing profiles than the metronome (pushed strokes earlier, laid-back strokes later). Also, overall the metronome reference led to earlier mean onsets than the instrumental reference, possibly related to the “negative mean asynchrony” phenomenon. Regarding sound, results revealed systematic differences across participants in the duration (snare) and intensity (snare and hi-hat) of strokes played using the different timing styles. Pattern also had an impact: drummers generally played the rhythmically more complex pattern 2 louder than the simpler pattern 1 (snare and kick). Overall, our results lend further evidence to the hypothesis that both temporal and sound-related features contribute to the indication of the timing of a rhythmic event in groove-based performance.

In this work, we present a method for generating sound-tracings using a mixture density recurrent neural network (MDRNN). A sound-tracing is a rendering of perceptual qualities of short sound objects through body motion. The model is trained on a dataset of single point sound-tracings with multimodal input data and learns to generate novel tracings. We use a second neural network classifier to show that the input sound can be identified from generated tracings. This is part of an ongoing research effort to examine the complex correlations between sound and movement and the possibility of modelling these relationships using deep learning.

People tend to perceive many and also salient similarities between musical sound and body motion in musical experience, as can be seen in countless situations of music performance or listening to music, and as has been documented by a number of studies in the past couple of decades. The so-called motor theory of perception has claimed that these similarity relationships are deeply rooted in human cognitive faculties, and that people perceive and make sense of what they hear by mentally simulating the body motion thought to be involved in the making of sound. In this paper, we survey some basic theories of sound-motion similarity in music, and in particular the motor theory perspective. We also present findings regarding sound-motion similarity in musical performance, in dance, in so-called sound-tracing (the spontaneous body motions people produce in tandem with musical sound), and in sonification, all in view of providing a broad basis for understanding sound-motion similarity in music.

Recording music-related motions in ecological valid situa- tions can be challenging. We investigate the performance of three devices providing 3D acceleration data, namely Axivity AX3, iPhone 4s and a Wii controller tracking rhythmic motions. The devices are benchmarked against an infrared motion capture system. The devices tracked simple and complex rhythmic motions to pre-recorded music and were evalu- ated both based on the data quality and also in terms of how suitable the systems seem for tracking music-related motions in real-world situa- tions. The various systems represent different trade offs with respect to timing, accuracy and precision.

A system for decentralized synchronization of musical agents is presented, inspired by Mirollo and Strogatz' pulse-coupled oscillator model of the synchronous flashing of certain species of firefly. While most previous work on pulse-coupled oscillators assume fixed and (close to) equal oscillator frequencies, the presented system tackles the challenge of different starting frequencies. Open source implementations in Puredata, Max, and Matlab are provided. Test results for setups of six nodes show that nodes reach a state of harmonic synchrony, where fire events coincide and oscillators display integer-ratio frequency relations.

This paper compares the use of two different technologies for controlling sound synthesis in real time: the infrared marker-based motion capture system OptiTrack and Xsens MVN, an inertial sensor-based motion capture suit. We present various quantitative comparisons between the data from the two systems and results from an experiment where a musician performed simple musical tasks with the two systems. Both systems are found to have their strengths and weaknesses, which we will present and discuss.

cote interne IRCAM: Nymoen11a; None / None; National audience; This paper investigates differences in the gestures people relate to pitched and non-pitched sounds respectively. An experiment has been carried out where participants were asked to move a rod in the air, pretending that moving it would create the sound they heard. By applying and interpreting the results from Canonical Correlation Analysis we are able to determine both simple and more complex correspondences between features of motion and features of sound in our data set. Particularly, the presence of a distinct pitch seems to influence how people relate gesture to sound. This identification of salient relationships between sounds and gestures contributes as a multi-modal approach to music information retrieval.

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.