R: stri_replace_all_fixed slow on big data set - is there an alternative? : I'm trying to stem ~4000 documents in R, by using the <b>stri_replace_all_fixed</b> function. However, it is VERY slow, since my dictionary of stemmed words consists of approx. 300k words. I am doing this because the documents are in danish and therefore the Porter Stemmer Algortihm is not useful (it is too aggressive). 

I have posted the code below. Does anyone know an alternative for doing this? 
Logic: Look at each word in each document -> If word = word from voc-table, then replace with tran-word. 

    ##Read in the dictionary
     voc <- read.table("danish.csv", header = TRUE, sep=";")
    #Using the library 'stringi' to make the stemming
     library(stringi)
    #Split the voc corpus and put the word and stem column into different corpus
     word <- Corpus(VectorSource(voc))[1]
     tran <- Corpus(VectorSource(voc))[2]
    #Using stri_replace_all_fixed to stem words
    ## !! NOTE THAT THE FOLLOWING STEP MIGHT TAKE A FEW MINUTES DEPENDING ON THE SIZE !! ##
     docs <- tm_map(docs, function(x) stri_replace_all_fixed(x, word, tran, vectorize_all = FALSE))

Structure of "voc" data frame:

           Word           Stem
    1      abandonnere    abandonner
    2      abandonnerede  abandonner
    3      abandonnerende abandonner
    ...
    313273 åsyns          åsyn

Thanks in advance! 