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Perception of string quartet synchronization.

Wing AM, Endo S, Yates T, Bradbury A - Front Psychol (2014)

Bottom Line: Timing variation in small group musical performance results from intentional, expressive, and unintentional, error components in individual player timing.Our results show that the between-player asynchrony variability giving 75% correct identification in Experiment 2 was significantly lower than in Experiment 1.This finding indicates that people are sensitive to both the degree of variance and the micro-structure of the time-series of the asynchronies caused by differences in correction gain when judging lack of togetherness in quartet performance.

View Article: PubMed Central - PubMed

Affiliation: SyMoN lab, School of Psychology, University of Birmingham Birmingham, UK.

ABSTRACT
Timing variation in small group musical performance results from intentional, expressive, and unintentional, error components in individual player timing. These timing fluctuations produce variability in between-player note asynchrony and require timing adjustments to keep the ensemble together. The size of the adjustments relative to the asynchrony (correction gain) affects the amount and nature of asynchrony variability. We present new listening tests to estimate thresholds for perception of between-player asynchrony variability and to determine whether listeners use differences in the nature of the variability, as well as in its magnitude, to judge asynchrony. In two experiments, computer-simulated ensemble performances of a 48-note excerpt from Haydn Op. 74 No. 1 were generated. Between-player note asynchrony was systematically manipulated in terms of level of within-player timing variability (Experiment 1) and correction gain (Experiment 2). On each trial, participants listened to two samples, one ("target") with more between-player asynchrony variability than the other ("test"), and reported which was "less together." In both experiments, the test sample correction gain was fixed at the statistically optimal value of 0.25 and the within-player timing variability was minimal (zero except for random variability in the initial note). In Experiment 1 the target correction gain was fixed at 0.25 and the timing variability was adjusted over trials by a staircase algorithm designed to converge on the level of asynchrony variability giving 75% correct identification. In Experiment 2 the timing variability in the target was set at half that in Experiment 1 and the correction gain was varied to converge on 75% correct identification. Our results show that the between-player asynchrony variability giving 75% correct identification in Experiment 2 was significantly lower than in Experiment 1. This finding indicates that people are sensitive to both the degree of variance and the micro-structure of the time-series of the asynchronies caused by differences in correction gain when judging lack of togetherness in quartet performance.

No MeSH data available.


Related in: MedlinePlus

Binned proportion of correct responses as a function of (left) the timing variability (Experiment 1) and (right) gain difference in non-target and target quartets (Experiment 2) calculated for a single participant.
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Figure 4: Binned proportion of correct responses as a function of (left) the timing variability (Experiment 1) and (right) gain difference in non-target and target quartets (Experiment 2) calculated for a single participant.

Mentions: Due to the random nature of the stimulus generation process, asynchrony variance can vary between stimuli generated using identical within-player timing variability (Experiment 1) or gain (Experiment 2) as illustrated in Figure 2C. To ensure that the between-player asynchrony variance of the stochastically generated stimulus was close to the theoretical value for the timing variability or gain value specified by the staircase, 10000 sets of time-series were generated for each set of simulation parameters before the experiment, and the mean asynchrony variance was determined at each level. The required simulation parameters for given asynchrony variances were then calculated using linear interpolation between the simulated mean asynchrony variances. If the resulting generated stimulus asynchrony variance (calculated per note, and averaged over all 48 notes) was outside a tolerance region of the theoretical variance plus or minus 10-7 s2, then new stimuli were generated until one resulted with asynchrony variance within the tolerance region. In Experiment 1 the asynchrony variance threshold at which the listener correctly identified the target on 75% of trials corresponding to [ = ThCENTRAL, α = 0.25] was measured by fitting the logistic function to the psychometric data consisting of binned fractional correct responses (Figure 4). In Experiment 2, the timing variability was fixed at half the level, i.e., [ = ThCENTRAL/2] corresponding to the threshold determined in Experiment 1, and the gain was controlled by the staircase algorithm to converge on 75% correct target identification.


Perception of string quartet synchronization.

Wing AM, Endo S, Yates T, Bradbury A - Front Psychol (2014)

Binned proportion of correct responses as a function of (left) the timing variability (Experiment 1) and (right) gain difference in non-target and target quartets (Experiment 2) calculated for a single participant.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4196478&req=5

Figure 4: Binned proportion of correct responses as a function of (left) the timing variability (Experiment 1) and (right) gain difference in non-target and target quartets (Experiment 2) calculated for a single participant.
Mentions: Due to the random nature of the stimulus generation process, asynchrony variance can vary between stimuli generated using identical within-player timing variability (Experiment 1) or gain (Experiment 2) as illustrated in Figure 2C. To ensure that the between-player asynchrony variance of the stochastically generated stimulus was close to the theoretical value for the timing variability or gain value specified by the staircase, 10000 sets of time-series were generated for each set of simulation parameters before the experiment, and the mean asynchrony variance was determined at each level. The required simulation parameters for given asynchrony variances were then calculated using linear interpolation between the simulated mean asynchrony variances. If the resulting generated stimulus asynchrony variance (calculated per note, and averaged over all 48 notes) was outside a tolerance region of the theoretical variance plus or minus 10-7 s2, then new stimuli were generated until one resulted with asynchrony variance within the tolerance region. In Experiment 1 the asynchrony variance threshold at which the listener correctly identified the target on 75% of trials corresponding to [ = ThCENTRAL, α = 0.25] was measured by fitting the logistic function to the psychometric data consisting of binned fractional correct responses (Figure 4). In Experiment 2, the timing variability was fixed at half the level, i.e., [ = ThCENTRAL/2] corresponding to the threshold determined in Experiment 1, and the gain was controlled by the staircase algorithm to converge on 75% correct target identification.

Bottom Line: Timing variation in small group musical performance results from intentional, expressive, and unintentional, error components in individual player timing.Our results show that the between-player asynchrony variability giving 75% correct identification in Experiment 2 was significantly lower than in Experiment 1.This finding indicates that people are sensitive to both the degree of variance and the micro-structure of the time-series of the asynchronies caused by differences in correction gain when judging lack of togetherness in quartet performance.

View Article: PubMed Central - PubMed

Affiliation: SyMoN lab, School of Psychology, University of Birmingham Birmingham, UK.

ABSTRACT
Timing variation in small group musical performance results from intentional, expressive, and unintentional, error components in individual player timing. These timing fluctuations produce variability in between-player note asynchrony and require timing adjustments to keep the ensemble together. The size of the adjustments relative to the asynchrony (correction gain) affects the amount and nature of asynchrony variability. We present new listening tests to estimate thresholds for perception of between-player asynchrony variability and to determine whether listeners use differences in the nature of the variability, as well as in its magnitude, to judge asynchrony. In two experiments, computer-simulated ensemble performances of a 48-note excerpt from Haydn Op. 74 No. 1 were generated. Between-player note asynchrony was systematically manipulated in terms of level of within-player timing variability (Experiment 1) and correction gain (Experiment 2). On each trial, participants listened to two samples, one ("target") with more between-player asynchrony variability than the other ("test"), and reported which was "less together." In both experiments, the test sample correction gain was fixed at the statistically optimal value of 0.25 and the within-player timing variability was minimal (zero except for random variability in the initial note). In Experiment 1 the target correction gain was fixed at 0.25 and the timing variability was adjusted over trials by a staircase algorithm designed to converge on the level of asynchrony variability giving 75% correct identification. In Experiment 2 the timing variability in the target was set at half that in Experiment 1 and the correction gain was varied to converge on 75% correct identification. Our results show that the between-player asynchrony variability giving 75% correct identification in Experiment 2 was significantly lower than in Experiment 1. This finding indicates that people are sensitive to both the degree of variance and the micro-structure of the time-series of the asynchronies caused by differences in correction gain when judging lack of togetherness in quartet performance.

No MeSH data available.


Related in: MedlinePlus