qdap (version 2.4.6)

syllable_sum: Syllabication

Description

syllable_sum - Count the number of syllables per row of text.

syllable_count - Count the number of syllables in a single text string.

polysyllable_sum - Count the number of polysyllables per row of text.

combo_syllable_sum - Count the number of both syllables and polysyllables per row of text.

Usage

syllable_sum(text.var, parallel = FALSE, ...)
syllable_count(
  text,
  remove.bracketed = TRUE,
  algorithm.report = FALSE,
  env = qdap::env.syl
)
polysyllable_sum(text.var, parallel = FALSE)
combo_syllable_sum(text.var, parallel = FALSE)

Value

syllable_sum - returns a vector of syllable counts per row.

syllable_count - returns a dataframe of syllable counts and algorithm/dictionary uses and, optionally, a report of words not found in the dictionary.

polysyllable_sum - returns a vector of polysyllable counts per row.

combo_syllable_sum - returns a dataframe of syllable and polysyllable counts per row.

Arguments

text.var

The text variable

parallel

logical. If TRUE attempts to run the function on multiple cores. Note that this may not mean a speed boost if you have one core or if the data set is smaller as the cluster takes time to create.

text

A single character vector of text.

remove.bracketed

logical. If TRUE brackets are removed from the analysis.

algorithm.report

logical. If TRUE generates a report of words not found in the dictionary (i.e., syllables were calculated with an algorithm).

env

A lookup environment to lookup the number of syllables in found words.

...

Other arguments passed to syllable_count.

Details

The worker function of all the syllable functions is syllable_count, though it is not intended for direct use on a transcript. This function relies on a combined dictionary lookup (based on the Nettalk Corpus (Sejnowski & Rosenberg, 1987)) and backup algorithm method.

References

Sejnowski, T.J., and Rosenberg, C.R. (1987). "Parallel networks that learn to pronounce English text" in Complex Systems, 1, 145-168.

Examples

if (FALSE) {
syllable_count("Robots like Dason lie.")
syllable_count("Robots like Dason lie.", algorithm.report = TRUE)

syllable_sum(DATA$state)
x1 <- syllable_sum(rajSPLIT$dialogue)
plot(x1)
cumulative(x1)

polysyllable_sum(DATA$state)
x2 <- polysyllable_sum(rajSPLIT$dialogue)
plot(x2)
cumulative(x2)

combo_syllable_sum(DATA$state)
x3 <- combo_syllable_sum(rajSPLIT$dialogue)
plot(x3) 
cumulative(x3)
}