Description Usage Format References Examples
Durational measurements on the Dutch prefix ont- in the Spoken Dutch Corpus.
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A data frame with 102 observations on the following 11 variables.
Word
a factor with the words as levels.
Frequency
a numeric vector with the word's logarithmically transformed frequency in the Spoken Dutch Corpus.
Speaker
a factor with speakers as levels.
Sex
a factor with levels female
and male
.
YearOfBirth
a numeric vector coding year of birth of the speaker - 1900.
DurationOfPrefix
a numeric vector for the duration of ont- in seconds
DurationPrefixVowel
a numeric vector for the duration of the vowel in the prefix in seconds.
DurationPrefixNasal
a numeric vector for the duration of the nasal in the prefix in seconds.
DurationPrefixPlosive
a numeric vector for the duration of the plosive in the prefix in seconds.
NumberOfSegmentsOnset
a numeric vector for the number of segments in the onset of the stem.
PlosivePresent
a factor with levels no
and yes
for whether the plosive is realized in the signal.
SpeechRate
a numeric vector coding speech rate in number of syllables per second.
Pluymaekers, M., Ernestus, M. and Baayen, R. H. (2005) Frequency and acoustic length: the case of derivational affixes in Dutch, Journal of the Acoustical Society of America, 118, 2561-2569.
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 35 36 37 38 39 40 | data(durationsOnt)
###### modeling the duration of the prefix
prefix.lm = lm(DurationOfPrefix ~ (YearOfBirth + SpeechRate) * Frequency,
data = durationsOnt)
summary(prefix.lm)
# ---- model criticism
plot(prefix.lm)
outliers = c(36, 35, 17, 72)
prefix.lm = lm(DurationOfPrefix ~ (YearOfBirth + SpeechRate) * Frequency,
data = durationsOnt[-outliers,])
summary(prefix.lm)
###### modeling the presence of the /t/
library(rms)
durationsOnt.dd = datadist(durationsOnt)
options(datadist = 'durationsOnt.dd')
plosive.lrm = lrm(PlosivePresent ~ SpeechRate + YearOfBirth,
data = durationsOnt, x = TRUE, y = TRUE)
plosive.lrm
validate(plosive.lrm, bw = TRUE, B = 200)
###### modeling the duration of the /n/
nasal.lm = lm(DurationPrefixNasal ~ PlosivePresent + Frequency +
YearOfBirth, data = durationsOnt)
summary(nasal.lm)
# ---- model criticism
plot(nasal.lm)
outliers = c(71, 28, 62, 33)
nasal.lm = lm(DurationPrefixNasal ~ PlosivePresent + Frequency +
YearOfBirth, data = durationsOnt[-outliers,])
summary(nasal.lm)
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