The function below, biGram(), calculates the bigram probability for any given word based on a given corpus. The output is logarithmic sum of the individual probabilities for each segmental bigram. The function requires two arguments, namely, a word (x) and a corpus/list of words. Some lines in the function below are based on the Portuguese Stress Lexicon. The function requires tidyverse.

To work with n-grams in general, I strongly recommend the excellent ngram package.


biGram = function(x, corpus){
  
  library(tidyverse)
  words = unlist(str_split(corpus, pattern = " "))
  words = str_replace_all(string = words, pattern = "-", replacement = "")
  words = str_replace_all(string = words, pattern = "'", replacement = "")
  
  x1 = str_split(x, pattern = "")[[1]]
  
  bigrams = c()
  bigrams[1] = paste("^", x1[1], sep = "")
  
  # Adding word-internal bigrams
  for(i in 1:(length(x1)-1)){
    seq = str_c(x1[i], x1[i+1], sep = "")
    bigrams[length(bigrams)+1] = seq
  }
  
  # Adding word-final bigram
  bigrams[length(bigrams)+1] = str_c(x1[length(x1)], "$", sep = "")
  
  # Variable for all probabilities
  probs = c()
  
  for(bigram in bigrams){
    probs[length(probs)+1] = sum(str_count(words, bigram)) / 
      sum(str_count(words, str_split(bigram, pattern = "")[[1]][1]))
  }
  
  return(log(prod(probs)))
}


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