Date: 2024-08-07

# The hunspell package: High-Performance Stemmer, Tokenizer, and Spell Checker for R

#### 2024-08-07

Hunspell is the spell checker library used by LibreOffice, OpenOffice, Mozilla Firefox, Google Chrome, Mac OS-X, InDesign, Opera, RStudio and many others. It provides a system for tokenizing, stemming and spelling in almost any language or alphabet. The R package exposes both the high-level spell-checker as well as low-level stemmers and tokenizers which analyze or extract individual words from various formats (text, html, xml, latex).

Hunspell uses a special dictionary format that defines which characters, words and conjugations are valid in a given language. The examples below use the (default) `"en_US"` dictionary. However each function can be used in another language by setting a custom dictionary in the `dict` parameter. See the section on dictionaries below.

## Spell Checking

Spell checking text consists of the following steps:

1. Parse a document by extracting (tokenizing) words that we want to check
2. Analyze each word by breaking it down in it’s root (stemming) and conjugation affix
3. Lookup in a dictionary if the word+affix combination if valid for your language
4. (optional) For incorrect words, suggest corrections by finding similar (correct) words in the dictionary

We can do each these steps manually or have Hunspell do them automatically.

### Check Individual Words

The `hunspell_check` and `hunspell_suggest` functions can test individual words for correctness, and suggest similar (correct) words that look similar to the given (incorrect) word.

    library(hunspell)

    # Check individual words
    words <- c("beer", "wiskey", "wine")
    correct <- hunspell_check(words)
    print(correct)

    [1]  TRUE FALSE  TRUE

    # Find suggestions for incorrect words
    hunspell_suggest(words[!correct])

    [[1]]
    [1] "whiskey"  "whiskery"

### Check Documents

In practice we often want to spell check an entire document at once by searching for incorrect words. This is done using the `hunspell` function:

    bad <- hunspell("spell checkers are not neccessairy for langauge ninjas")
    print(bad[[1]])

    [1] "neccessairy" "langauge"

    hunspell_suggest(bad[[1]])

    [[1]]
    [1] "necessary"   "necessarily"

    [[2]]
    [1] "language" "melange"

Besides plain text, `hunspell` supports various document formats, such as html or latex:

    download.file("https://arxiv.org/e-print/1406.4806v1", "1406.4806v1.tar.gz",  mode = "wb")
    untar("1406.4806v1.tar.gz", "content.tex")
    text <- readLines("content.tex", warn = FALSE)
    bad_words <- hunspell(text, format = "latex")
    sort(unique(unlist(bad_words)))

     [1] "auth"              "CORBA"             "cpu"               "cran"              "cron"
     [6] "css"               "csv"               "CTRL"              "DCOM"              "de"
    [11] "dec"               "decompositions"    "dir"               "DOM"               "DSL"
    [16] "eol"               "ESC"               "facto"             "grDevices"         "httpuv"
    [21] "ignorable"         "interoperable"     "JRI"               "js"                "json"
    [26] "jsonlite"          "knitr"             "md"                "memcached"         "mydata"
    [31] "myfile"            "nondegenerateness" "OAuth"             "ocpu"              "opencpu"
    [36] "OpenCPU"           "pandoc"            "pb"                "php"               "png"
    [41] "prescripted"       "priori"            "protobuf"          "rApache"           "rda"
    [46] "rds"               "reproducibility"   "Reproducibility"   "RinRuby"           "RInside"
    [51] "rlm"               "rmd"               "rnorm"             "rnw"               "RPC"
    [56] "RProtoBuf"         "rpy"               "Rserve"            "RStudio"           "saveRDS"
    [61] "scalability"       "scalable"          "schemas"           "se"                "sep"
    [66] "SIGINT"            "STATA"             "stateful"          "Stateful"          "statefulness"
    [71] "stdout"            "STDOUT"            "suboptimal"        "svg"               "sweave"
    [76] "tex"               "texi"              "tmp"               "toJSON"            "urlencoded"
    [81] "www"               "xyz"

### Check PDF files

Use the text-extraction from the `pdftools` package to spell check text from PDF files!

    text <- pdftools::pdf_text('https://www.gnu.org/licenses/quick-guide-gplv3.pdf')
    bad_words <- hunspell(text)
    sort(unique(unlist(bad_words)))

     [1] "Affero"        "AGPLed"        "cryptographic" "DRM"           "fsf"           "GPLed"         "GPLv"
     [8] "ISC"           "OpenSolaris’"  "opments"       "tivoization"   "Tivoization"   "tributing"     "users’"

### Check Manual Pages

The `spelling` package builds on hunspell and has a wrapper to spell-check manual pages from R packages. Results might contain a lot of false positives for technical jargon, but you might also catch a typo or two. Point it to the root of your source package:

    spelling::spell_check_package("~/workspace/V8")

      WORD          FOUND IN
    ECMA          V8.Rd:16, description:2,4
    ECMAScript    description:2
    emscripten    description:5
    htmlwidgets   JS.Rd:16
    JSON          V8.Rd:33,38,39,57,58,59,120
    jsonlite      V8.Rd:42
    Ooms          V8.Rd:41,120
    Xie           JS.Rd:26
    Yihui         JS.Rd:26

## Morphological Analysis

In order to lookup a word in a dictionary, hunspell needs to break it down in a stem (stemming) and conjugation affix. The `hunspell` function does this automatically but we can also do it manually.

### Stemming Words

The `hunspell_stem` looks up words from the dictionary which match the root of the given word. Note that the function returns a list because some words can have multiple matches.

    # Stemming
    words <- c("love", "loving", "lovingly", "loved", "lover", "lovely")
    hunspell_stem(words)

    [[1]]
    [1] "love"

    [[2]]
    [1] "loving" "love"

    [[3]]
    [1] "loving"

    [[4]]
    [1] "loved" "love"

    [[5]]
    [1] "lover" "love"

    [[6]]
    [1] "lovely" "love"

### Analyzing Words

The `hunspell_analyze` function is similar, but it returns both the stem and the affix syntax of the word:

    hunspell_analyze(words)

    [[1]]
    [1] " st:love"

    [[2]]
    [1] " st:loving"    " st:love fl:G"

    [[3]]
    [1] " st:loving fl:Y"

    [[4]]
    [1] " st:loved"     " st:love fl:D"

    [[5]]
    [1] " st:lover"     " st:love fl:R"

    [[6]]
    [1] " st:lovely"    " st:love fl:Y"

## Tokenizing

To support spell checking on documents, Hunspell includes parsers for various document formats, including text, html, xml, man or latex. The Hunspell package also exposes these tokenizers directly so they can be used for other application than spell checking.

    text <- readLines("content.tex", warn = FALSE)
    allwords <- hunspell_parse(text, format = "latex")

    # Third line (title) only
    print(allwords[[3]])

     [1] "The"        "OpenCPU"    "System"     "Towards"    "a"          "Universal"  "Interface"  "for"
     [9] "Scientific" "Computing"  "through"    "Separation" "of"         "Concerns"

### Summarizing Text

In text analysis we often want to summarize text via it’s stems. For example we can count words for display in a wordcloud:

    allwords <- hunspell_parse(janeaustenr::prideprejudice)
    stems <- unlist(hunspell_stem(unlist(allwords)))
    words <- sort(table(stems), decreasing = TRUE)
    print(head(words, 30))

    stems
          the        to        of       and         a         i         h         I        in       was       she
         4402      4305      3611      3585      3135      2929      2233      2069      1881      1846      1711
           it      that       not       you        he        hi        be       had        Mr       for      with
         1640      1579      1429      1366      1336      1271      1241      1177      1129      1064      1053
          but      have        on        at       him        my        by Elizabeth
         1002       938       931       787       764       719       636       635

Most of these are stop words. Let’s filter these out:

    df <- as.data.frame(words)
    df$stems <- as.character(df$stems)
    stops <- df$stems %in% stopwords::stopwords(source="stopwords-iso")
    wcdata <- head(df[!stops,], 150)
    print(wcdata, max = 40)

            stems Freq
    8           I 2069
    20         Mr 1129
    30  Elizabeth  635
    48      Darcy  418
    63     sister  294
    64       Jane  292
    68       Miss  281
    72       lady  265
    76         It  247
    79         He  235
    85       time  224
    87         ha  221
    96        aft  200
    105     happy  183
    107   Collins  180
    112       bee  175
    115       day  174
    117     Lydia  171
    119      feel  167
    120    friend  166
     [ reached 'max' / getOption("max.print") -- omitted 130 rows ]

    library(wordcloud2)
    names(wcdata) <- c("word", "freq")
    wcdata$freq <- (wcdata$freq)^(2/3)
    wordcloud2(wcdata)

    Error in loadNamespace(name): there is no package called 'webshot'

## Hunspell Dictionaries

Hunspell is based on MySpell and is backward-compatible with MySpell and aspell dictionaries. Chances are your dictionaries in your language are already available on your system!

A Hunspell dictionary consists of two files:

- The `[lang].aff` file specifies the affix syntax for the language
- The `[lang].dic` file contains a wordlist formatted using syntax from the aff file.

Typically both files are located in the same directory and share the same filename, for example `en_GB.aff` and `en_GB.dic`. The `list_dictionaries()` function lists available dictionaries in the current directory and standard system paths where dictionaries are usually installed.

    list_dictionaries()

    [1] "en_AU" "en_CA" "en_GB" "en_US"

The `dictionary` function is then used to load any of these available dictionaries:

    dictionary("en_GB")

    <hunspell dictionary>
     affix: /Users/jeroen/Library/R/arm64/4.4/library/hunspell/dict/en_GB.aff
     dictionary: /Users/jeroen/Library/R/arm64/4.4/library/hunspell/dict/en_GB.dic
     encoding: UTF-8
     wordchars: ’
     added: 0 custom words

If the files are not in one of the standard paths you can also specify the full path to either or both the dic and aff file:

    dutch <- dictionary("~/workspace/Dictionaries/Dutch.dic")
    print(dutch)

    <hunspell dictionary>
     affix: /Users/jeroen/workspace/Dictionaries/Dutch.aff
     dictionary: /Users/jeroen/workspace/Dictionaries/Dutch.dic
     encoding: UTF-8
     wordchars: '-./0123456789\ĳ’

### Setting a Language

The hunspell R package includes dictionaries for `en_US` and `en_GB`. So if you you don’t speak `en_US` you can always switch to the British English:

    hunspell("My favourite colour to visualise is grey")

    [[1]]
    [1] "favourite" "colour"    "visualise" "grey"

    hunspell("My favourite colour to visualise is grey", dict = 'en_GB')

    [[1]]
    character(0)

If you want to use another language you need to make sure that the dictionary is available from your system. The `dictionary` function is used to read in dictionary.

    dutch <- dictionary("~/workspace/Dictionaries/Dutch.dic")
    hunspell("Hij heeft de klok wel horen luiden, maar weet niet waar de klepel hangt", dict = dutch)

Note that if the `dict` argument is a string, it will be passed on to the `dictionary` function.

### Installing Dictionaries in RStudio

RStudio users can install various dictionaries via the “Global Options” menu of the IDE. Once these dictionaries are installed they become available to the `hunspell` and `spelling` package as well.

### Dictionaries on Linux

The best way to install dictionaries on Linux is via the system package manager. For example on if you would like to install the Austrian-German dictionary on Debian or Ubuntu you either need the `hunspell-de-at` or `myspell-de-at` package:

    sudo apt-get install hunspell-de-at

On Fedora and CentOS / RHEL all German dialects are included with the `hunspell-de` package

    sudo yum install hunspell-de

After installing this you should be able to load the dictionary:

    dict <- dictionary('de_AT')

If that didn’t work, verify that the dictionary files were installed in one of the system directories (usually `/usr/share/myspell` or `/usr/share/hunspell`).

### Custom Dictionaries

If your system does not provide standard dictionaries you need to download them yourself. There are a lot of places that provide quality dictionaries.

- SCOWL
- OpenOffice
- LibreOffice
- titoBouzout
- wooorm

On OS-X it is recommended to put the files in `~/Library/Spelling/` or `/Library/Spelling/`. However you can also put them in your project working directory, or any of the other standard locations. If you wish to store your dictionaries somewhere else, you can make hunspell find them by setting the `DICPATH` environment variable. The `hunspell:::dicpath()` shows which locations your system searches:

    Sys.setenv(DICPATH = "/my/custom/hunspell/dir")
    hunspell:::dicpath()

     [1] "/my/custom/hunspell/dir"
     [2] "/Users/jeroen/Library/R/arm64/4.4/library/hunspell/dict"
     [3] "/Users/jeroen/Library/Spelling"
     [4] "/usr/local/share/hunspell"
     [5] "/usr/local/share/myspell"
     [6] "/usr/local/share/myspell/dicts"
     [7] "/usr/share/hunspell"
     [8] "/usr/share/myspell"
     [9] "/usr/share/myspell/dicts"
    [10] "/Library/Spelling"
    [11] "/Applications/RStudio.app/Contents/Resources/app/resources/dictionaries"
    [12] "~/.config/rstudio/dictionaries/languages-system"
    [13] "~/.config/rstudio/dictionaries/languages-user"