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)
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.TRUE
brackets are removed from
the analysis.TRUE
generates a report of words
not found in the dictionary (i.e., syllables were calculated with an
algorithm).syllable_count
.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.
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.
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.
Sejnowski, T.J., and Rosenberg, C.R. (1987). "Parallel networks that learn to pronounce English text" in Complex Systems, 1, 145-168.
## <strong>Not run</strong>: # 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) # ## <strong>End(Not run)</strong>