envirosound {eba} | R Documentation |

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.

`data(envirosound)`

A data frame containing 74 observations on 2 variables:

- unpleasantness
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.- rt
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.

```
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
)
```

[Package *eba* version 1.10-0 Index]