syllabifyr

The goal of syllabifyr is to provide tidy syllabification of phonetic transcriptions. So far, only CMU dict transcriptions are supported.

I’ve largely utilized the same approach as Kyle Gorman’s python implementation

Installation

syllabifyr is now on Cran

install.packages("syllabifyr")

You can also install syllabifyr from github with:

# install.packages("devtools")
devtools::install_github("JoFrhwld/syllabifyr")

Example

library(syllabifyr)
syllabify("AO0 S T R EY1 L Y AH0")
#> # A tibble: 8 × 4
#>    syll part    phone stress
#>   <dbl> <chr>   <chr> <chr> 
#> 1     1 nucleus AO    0     
#> 2     2 onset   S     1     
#> 3     2 onset   T     1     
#> 4     2 onset   R     1     
#> 5     2 nucleus EY    1     
#> 6     2 coda    L     1     
#> 7     3 onset   Y     0     
#> 8     3 nucleus AH    0
syllabify(c("AO0", "S", "T", "R", "EY1", "L", "Y", "AH0"))
#> # A tibble: 8 × 4
#>    syll part    phone stress
#>   <dbl> <chr>   <chr> <chr> 
#> 1     1 nucleus AO    0     
#> 2     2 onset   S     1     
#> 3     2 onset   T     1     
#> 4     2 onset   R     1     
#> 5     2 nucleus EY    1     
#> 6     2 coda    L     1     
#> 7     3 onset   Y     0     
#> 8     3 nucleus AH    0

library(tidyverse)
#> Warning: package 'ggplot2' was built under R version 4.3.1
#> Warning: package 'lubridate' was built under R version 4.3.1

syllabficiation <- tribble(~word, ~transcription,
                          "Alaska", "AH0 L AE1 S K AH0",
                          "constraint", "K AH0 N S T R EY1 N T",
                          "canyon", "K AE1 N Y AH0 N",
                          "value", "V AE1 L Y UW0")%>%
                        mutate(syllable_df = map(transcription, syllabify))
syllabficiation$syllable_df[[1]]
#> # A tibble: 6 × 4
#>    syll part    phone stress
#>   <dbl> <chr>   <chr> <chr> 
#> 1     1 nucleus AH    0     
#> 2     2 onset   L     1     
#> 3     2 nucleus AE    1     
#> 4     2 coda    S     1     
#> 5     3 onset   K     0     
#> 6     3 nucleus AH    0
syllabficiation$syllable_df[[2]]
#> # A tibble: 9 × 4
#>    syll part    phone stress
#>   <dbl> <chr>   <chr> <chr> 
#> 1     1 onset   K     0     
#> 2     1 nucleus AH    0     
#> 3     1 coda    N     0     
#> 4     2 onset   S     1     
#> 5     2 onset   T     1     
#> 6     2 onset   R     1     
#> 7     2 nucleus EY    1     
#> 8     2 coda    N     1     
#> 9     2 coda    T     1
syllabficiation$syllable_df[[3]]
#> # A tibble: 6 × 4
#>    syll part    phone stress
#>   <dbl> <chr>   <chr> <chr> 
#> 1     1 onset   K     1     
#> 2     1 nucleus AE    1     
#> 3     1 coda    N     1     
#> 4     2 onset   Y     0     
#> 5     2 nucleus AH    0     
#> 6     2 coda    N     0
syllabficiation$syllable_df[[4]]
#> # A tibble: 5 × 4
#>    syll part    phone stress
#>   <dbl> <chr>   <chr> <chr> 
#> 1     1 onset   V     1     
#> 2     1 nucleus AE    1     
#> 3     1 coda    L     1     
#> 4     2 onset   Y     0     
#> 5     2 nucleus UW    0