finalDevoicing {languageR} | R Documentation |
Final Devoicing in Dutch
Description
Phonological specifications for onset, nucleus and offset for 1697 Dutch monomorphemic words with a final obstruent. These final obstruents may exhibit a voicing alternation that is traditionally described as syllable-final devoicing: underlying /d/ in /hond/ becomes a /t/ when syllable-final ([hOnt]) and remains a /d/ otherwise ([hOn-den]).
Usage
data(finalDevoicing)
Format
A data frame with 1697 observations on the following 9 variables.
Word
a factor with the words as levels.
Onset1Type
a factor for the first consonant in the onset, with levels
None
,Obstruent
andSonorant
.Onset2Type
a factor for the second consonant in the onset, with levels
None
,Obstruent
andSonorant
.VowelType
a factor describing the vowel with levels
iuy
,long
andshort
.ConsonantType
a factor for the first consonant in the offset, with levels
None
,Obstruent
andSonorant
.Obstruent
a factor describing place and manner of articulation of the final obstruent, with levels
F
(/f,v/),P
(/p,b/),S
(/s,z/),T
(/t,d/) andX
(/x,g/).Nsyll
a numeric vector for the number of syllables in the word.
Stress
a factor with levels
A
(antepenult),F
(final) andP
(penult).Voice
a factor with levels
voiced
andvoiceless
.
References
Ernestus, M. and Baayen, R. H. (2003) Predicting the unpredictable: Interpreting neutralized segments in Dutch, Language, 79, 5-38.
Examples
## Not run:
data(finalDevoicing)
library(rpart)
# ---- CART tree
finalDevoicing.rp = rpart(Voice ~ ., data = finalDevoicing[ , -1])
plotcp(finalDevoicing.rp)
finalDevoicing.pruned = prune(finalDevoicing.rp, cp = 0.021)
plot(finalDevoicing.pruned, margin = 0.1, compress = TRUE)
text(finalDevoicing.pruned, use.n = TRUE, pretty = 0, cex=0.8)
# ---- logistic regression
library(rms)
finalDevoicing.dd = datadist(finalDevoicing)
options(datadist='finalDevoicing.dd')
finalDevoicing.lrm = lrm(Voice ~ VowelType + ConsonantType + Obstruent +
Nsyll + Stress + Onset1Type + Onset2Type, data = finalDevoicing)
anova(finalDevoicing.lrm)
# ---- model simplification
fastbw(finalDevoicing.lrm)
finalDevoicing.lrm = lrm(Voice ~ VowelType + ConsonantType +
Obstruent + Nsyll, data = finalDevoicing, x = TRUE, y = TRUE)
plot(Predict(finalDevoicing.lrm))
# ---- model validation
validate(finalDevoicing.lrm, B = 200)
## End(Not run)