syllable_sum | R Documentation |
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.
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)
text.var |
The text variable |
parallel |
logical. If |
text |
A single character vector of text. |
remove.bracketed |
logical. If |
algorithm.report |
logical. If |
env |
A lookup environment to lookup the number of syllables in found words. |
... |
Other arguments passed to |
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.
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.
Sejnowski, T.J., and Rosenberg, C.R. (1987). "Parallel networks that learn to pronounce English text" in Complex Systems, 1, 145-168.
## Not run:
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)
## End(Not run)
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