syllable

syllable is a small collection of tools for counting syllables and polysyllables. The tools rely primarily on data.table hash table lookups, resulting in fast syllable counting.

Table of Contents

• Main Functions
  • Actions
  • Objects
  • Putting It Together
• Installation
• Contact
• Examples
  • Count Syllables In a String
  • Count Syllables In a Vector of Strings
  • Sum the Syllables In a Vector of Strings by Grouping Variable(s)
  • Tally the Short/Poly-Syllabic Words by Group(s)
  • Readability Word Statistics by Grouping Variable(s)
  • Visualize Poly Syllable Distributions
  • Visualize Poly Syllable Distributions by Group

Main Functions

The main functions follow the format of action_object.

Actions

The following table outlines the actions. Example Output correspond to this string: "I like chicken sandwiches.".

* The addition of _mono, _di, _poly _short (monosyllabic + disyllabic), or _both (short & pollysyllabic) to tally allows the user specify what syllable attribute is being tallied.

Objects

The following table outlines the objects acted upon:

* The addition of _by to vector allows the user to aggregate by one or more vectors of grouping variables.

Putting It Together

The function count_vector will provide a vector of integer counts for each word in a string. For this reason count_vector will return a list of integer vector counts.

count_vector(c("I like it.", "Look out!"))

## $`1`
## [1] 1 1 1
## 
## $`2`
## [1] 1 1

Each of the main functions is optimized to do its task efficiently. While one could use sum(count_vector(x)) and achieve the same results as sum_vector(x) it would be less efficient.

The available syllable functions that follow the format of action_object are:

Available Variable Functions

Installation

To download the development version of syllable:

Download the zip ball or tar ball, decompress and run R CMD INSTALL on it, or use the pacman package to install the development version:

if (!require("pacman")) install.packages("pacman")
pacman::p_load_gh(
    'trinker/lexicon',
    'trinker/textclean',
    'trinker/textshape',
    'trinker/syllable'
)

Contact

You are welcome to:

• submit suggestions and bug-reports at: https://github.com/trinker/syllable/issues
  
• send a pull request on: https://github.com/trinker/syllable/
  
• compose a friendly e-mail to: tyler.rinker@gmail.com
  

Examples

The following examples demonstrate the functionality of a select sample of syllable functions.

Count Syllables In a String

Counts the number of syllables for each word in a string.

count_string("I like chicken and eggs for breakfast")

## [1] 1 1 2 1 1 1 2

Count Syllables In a Vector of Strings

sents <- c("I like chicken.", "I want eggs benidict for breakfast.")
count_vector(sents)

## $`1`
## [1] 1 1 2
## 
## $`2`
## [1] 1 1 1 3 1 2

Map(function(x, y) setNames(x, y),
   count_vector(sents),
   strsplit(gsub("[^a-z ]", "", tolower(sents)), "\\s+")
)

## $`1`
##       i    like chicken 
##       1       1       2 
## 
## $`2`
##         i      want      eggs  benidict       for breakfast 
##         1         1         1         3         1         2

Sum the Syllables In a Vector of Strings by Grouping Variable(s)

dat <- data.frame(
   text = c("I like chicken.", "I want eggs benedict for breakfast.", "Really?"),
   group = c("A", "B", "A")
)
sum_vector_by(dat$text, dat$group)

##    group n.words count
## 1:     A       4     7
## 2:     B       6     9

Tally the Short/Poly-Syllabic Words by Group(s)

dat <- data.frame(
   text = c("I like excellent chicken.", "I want eggs benedict now.", "Really?"),
   group = c("A", "B", "A")
)
tally_both_vector_by(dat$text, dat$group)

##    group n.words short poly
## 1:     A       5     3    2
## 2:     B       5     4    1

with(presidential_debates_2012, tally_both_vector_by(dialogue, person))

##       person n.words short poly
## 1:     OBAMA   18319 16286 2033
## 2:    ROMNEY   19924 17858 2066
## 3:   CROWLEY    1672  1525  147
## 4:    LEHRER     765   674   91
## 5:  QUESTION     583   486   97
## 6: SCHIEFFER    1445  1289  156

Readability Word Statistics by Grouping Variable(s)

with(presidential_debates_2012, readability_word_stats_by(dialogue, list(person, time)))

##        person   time n.sents n.words n.chars n.sylls n.shorts n.polys
##  1:     OBAMA time 1     179    3599   16002    5221     3221     378
##  2:     OBAMA time 2     494    7477   32459   10654     6696     781
##  3:     OBAMA time 3     405    7243   32288   10675     6369     874
##  4:    ROMNEY time 1     279    4085   17984    5875     3646     439
##  5:    ROMNEY time 2     560    7536   32504   10720     6788     748
##  6:    ROMNEY time 3     569    8303   35824   11883     7424     879
##  7:   CROWLEY time 2     165    1672    6904    2308     1525     147
##  8:    LEHRER time 1      87     765    3256    1087      674      91
##  9:  QUESTION time 2      40     583    2765     930      486      97
## 10: SCHIEFFER time 3     133    1445    6234    2058     1289     156
##     n.complexes
##  1:         378
##  2:         781
##  3:         873
##  4:         439
##  5:         746
##  6:         878
##  7:         147
##  8:          91
##  9:          97
## 10:         156

Visualize Poly Syllable Distributions

if (!require("pacman")) install.packages("pacman")
pacman::p_load(dplyr, ggplot2, scales)

tally_both_vector(presidential_debates_2012$dialogue) %>%
    mutate(Duration = 1:length(poly)) %>%
    rowwise() %>%
    filter((short + poly) > 4) %>%
    mutate(
        short = short/(short+poly),
        poly = 1 - short,
        size = poly > .3
    ) %>%
    ggplot(aes(Duration, poly)) +
        geom_text(aes(label = Duration, size = size, color = size)) +
        coord_flip() +
        scale_size_manual(values = c(1.5, 2.5), guide=FALSE) +
        scale_color_manual(values = c("grey75", "black"), guide=FALSE) +
        scale_x_reverse() +
        scale_y_continuous(label = scales::percent) +
        ylab("Poly-syllabic") +
        xlab("Duration (sentences)") +
        theme_bw() 

Visualize Poly Syllable Distributions by Group

if (!require("pacman")) install.packages("pacman")
pacman::p_load(dplyr, ggplot2, tidyr, scales)

with(presidential_debates_2012, tally_both_vector_by(dialogue, list(person, time))) %>%
    mutate(
        person_time = paste(person, time, sep = "-"),
        short = short/(short+poly),
        poly = 1 - short
    ) %>%
    arrange(poly) %>%
    mutate(person_time = factor(person_time, levels = person_time)) %>%
    gather(type, prop, c(short, poly)) %>%
    ggplot(aes(person_time, weight = prop, fill = type)) +
        geom_bar() +
        coord_flip() +        
        scale_y_continuous(label = scales::percent) +
        scale_fill_discrete(name="Syllable\nType") +
        xlab("Person & Time") +
        ylab("Usage") +
        theme_bw()