EyeScout: Active Eye Tracking for Position and Movement Independent Gaze Interaction with Large Public Displays

While gaze holds a lot of promise for hands-free interaction with public displays, remote eye trackers with their confined tracking box restrict users to a single stationary position in front of the display. We present EyeScout, an active eye tracking system that combines an eye tracker mounted on a rail system with a computational method to automatically detect and align the tracker with the user's lateral movement. EyeScout addresses key limitations of current gaze-enabled large public displays by offering two novel gaze-interaction modes for a single user: In "Walk then Interact" the user can walk up to an arbitrary position in front of the display and interact, while in "Walk and Interact" the user can interact even while on the move. We report on a user study that shows that EyeScout is well perceived by users, extends a public display's sweet spot into a sweet line, and reduces gaze interaction kick-off time to 3.5 seconds -- a 62% improvement over state of the art solutions. We discuss sample applications that demonstrate how EyeScout can enable position and movement-independent gaze interaction with large public displays

Drum Groove Corpora

Patterned microtiming deviations from metronomic regularity are ubiquitous in the performance of metered music. The relevance of microtiming to the perception of music has been studied since the 1980s. Most recently, microtiming has been investigated as a cause of groove (i.e., the pleasant urge to move in response to music). The study of microtiming relies on the availability of microtiming data. This report presents three large corpora of onset timings derived from drum kit performances in popular Anglo-American popular music styles. These data are made freely available (CC 4.0 license) to provide a resource for use by analysts and experimenters alike. They offer a common point of reference for future studies into the temporal facets of music performance. The datasets adhere to FAIR principles; they thus facilitate replication of analyses and experimental stimuli

Modelling perceived syncopation in popular music drum patterns

Recent studies suggest that rhythmic syncopation is a relevant predictor for groove. In order to validate these claims, a reliable measure of rhythmic syncopation is required. This article investigates whether a particular notation-based model for estimating syncopation in Western popular music drum patterns adequately predicts perceived syncopation. A listening experiment was carried out with 25 professional musicians. Six popular music drum patterns were presented to the participants in all 15 pairwise combinations, and the participants chose the pattern from each pair that was more syncopated (win), compared to the other pattern (lose). Perceived syncopation was defined as the proportion of wins for each stimulus. The experiment showed that the model works well in general, but that it overemphasises the weight of syncopes on weak metric positions. This exaggerates the syncopation value of one particular drum pattern and generally leads to inflated syncopation values in the upper syncopation range. In consequence, the fit between the model and perceived syncopation was poor, even when flexible logarithmic functions ( χ 4 2 = 26.980 , p < .001) or exponential approach functions ( χ 4 2 = 28.344 , p < .001) were used to link the model predictions to perceived syncopation. The model was revised and a numeric optimisation process was carried out to improve its fit. The revised model produces syncopation estimates that have a linear relationship with the perceived syncopation measures and a good fit with the data ( χ 3 2 = 2.537 , p = .469). However, this revised model is based on only six drum patterns that cover a very limited range of rhythmic phenomena. In order to create a general model of syncopation in popular music drum patterns, further modelling work is necessary that involves a larger number and a wider variety of patterns

Groove in drum patterns as a function of both rhythmic properties and listeners' attitudes.

Music psychology defines groove as humans' pleasureable urge to move their body in synchrony with music. Past research has found that rhythmic syncopation, event density, beat salience, and rhythmic variability are positively associated with groove. This exploratory study investigates the groove effect of 248 reconstructed drum patterns from different popular music styles (pop, rock, funk, heavy metal, rock'n'roll, hip hop, soul, R&B). It aims at identifying factors that might be relevant for groove and worth investigating in a controlled setting in the future. Drum patterns of eight bars duration, chosen from 248 popular music tracks, have been transcribed and audio reconstructions have been created on the basis of sound samples. During an online listening experiment, 665 participants rated the reconstructions a total of 8,329 times using a groove questionnaire. Results show that, among 15 tested variables, syncopation (R2 = 0.010) and event density (R2 = 0.011) were positively associated with the groove ratings. These effects were stronger in participants who were music professionals, compared to amateur musicians or mere listeners. A categorisation of the stimuli according to structural aspects was also associated with groove (R2 = 0.018). Beat salience, residual microtiming and rhythmic variability showed no effect on the groove ratings. Participants' familiarity with a drum pattern had a positive influence on the groove ratings (η2 = 0.051). The largest isolated effect was measured for participants' style bias (R2 = 0.123): groove ratings tended to be high if participants had the impression that the drum pattern belonged to a style they liked. Combined, the effects of style bias and familiarity (R2 = 0.152) exceeded the other effects as predictors for groove by a wide margin. We conclude that listeners' taste, musical biographies and expertise have a strong effect on their groove experience. This motivates groove research not to focus on the music alone, but to take the listeners into account as well

Groove in drum patterns as a function of both rhythmic properties and listeners' attitudes

<p>Data set for article "Groove in drum patterns as a function of both rhythmic properties and listeners' attitudes".</p

Stimuli- and participant-related effects on <i>Groove</i>.

<p>Stimuli- and participant-related effects on <i>Groove</i>.</p

Questionnaire response items with inter-item correlations and factor loadings.

<p>Questionnaire response items with inter-item correlations and factor loadings.</p

Pattern category × expertise interaction plot.

<p><i>Groove</i> ratings as a function of <i>Pattern Category</i>, grouped by <i>Expertise</i>. Error bars are the standard error of the mean. Mean <i>Beat Recognition</i> and <i>Rhythmic Interest</i> ratings are given below each category.</p

Study flow diagram.

<p>Collection and triage of survey data.</p