languageR (version 1.5.0)

finalDevoicing: 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 and Sonorant.

Onset2Type

a factor for the second consonant in the onset, with levels None, Obstruent and Sonorant.

VowelType

a factor describing the vowel with levels iuy, long and short.

ConsonantType

a factor for the first consonant in the offset, with levels None, Obstruent and Sonorant.

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/) and X (/x,g/).

Nsyll

a numeric vector for the number of syllables in the word.

Stress

a factor with levels A (antepenult), F (final) and P (penult).

Voice

a factor with levels voiced and voiceless.

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)
# }