Description Usage Format Details Source References See Also Examples
Zimmer et al. (2004) investigated the auditory unpleasantness of twelve short binaural recordings (Johannsen and Prante, 2001); recordings were presented via headphones to 74 participants.
1 |
A data frame containing 74 observations on 2 variables:
paired comparison of class paircomp
;
judgments for all 66 paired comparisons from 12 recordings:
circular saw, stadium, dentist's drill, waterfall, ship's horn, stone in
well, typewriter, hooves, fan, howling wind, tyre on gravel, wasp.
median response time.
Details of the recordings, including psychoacoustic metrics, are available
as an attribute of the unpleasantness
variable (see Examples).
Zimmer, K., Ellermeier, W., & Schmid, C. (2004). Using probabilistic choice models to investigate auditory unpleasantness. Acta Acustica united with Acustica, 90(6), 1019–1028.
Johannsen, K., & Prante, H.U. (2001). Environmental sounds for psychoacoustic testing. Acta Acustica united with Acustica, 87(2), 290–293.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | requireNamespace("psychotools")
data(envirosound)
set.seed(1019)
## Choice-model representation of unpleasantness
mat <- summary(envirosound$unpleasantness, pcmatrix = TRUE)
strans(mat)
btl1 <- eba(mat)
eba1 <- eba(mat, A = list(c(1, 13), c(2, 13), c(3, 13), c(4, 13),
c(5, 13), c(6, 13), c(7, 13), c(8, 13),
c(9, 13), c(10, 13), c(11, 13), 12))
eba2 <- eba(mat, A = list(c(1, 13), c(2, 13), c(3, 13), c(4, 13),
c(5, 13), c(6, 13), c(7, 13, 14), c(8, 13, 14),
c(9, 13, 14), c(10, 13, 14), c(11, 13, 14), 12),
s = runif(14))
anova(btl1, eba1, eba2)
sounds <- psychotools::covariates(envirosound$unpleasantness)
sounds$u <- 10 * uscale(eba2, norm = 9) # u(fan) := 10
plot(magnitude ~ u, sounds, log = "x", type = "n",
xlab = "Indirect scaling (EBA model)",
ylab = "Direct magnitude estimation",
main = "Auditory unpleasantness of environmental sound")
mtext("(Zimmer et al., 2004)", line = 0.5)
abline(lm(magnitude ~ log10(u), sounds))
text(magnitude ~ u, sounds, labels = abbreviate(rownames(sounds), 4))
## Predicting unpleasantness from psychoacoustic metrics
summary(
lm(log(u) ~ scale(sharpness, scale = FALSE) +
scale(roughness, scale = FALSE):I(loudness.5 > 27),
sounds[-12, ]) # w/o wasp
)
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