Title: | High-Performance Stemmer, Tokenizer, and Spell Checker |
---|---|
Description: | Low level spell checker and morphological analyzer based on the famous 'hunspell' library <https://hunspell.github.io>. The package can analyze or check individual words as well as parse text, latex, html or xml documents. For a more user-friendly interface use the 'spelling' package which builds on this package to automate checking of files, documentation and vignettes in all common formats. |
Authors: | Jeroen Ooms [aut, cre], Authors of libhunspell [cph] (see AUTHORS file) |
Maintainer: | Jeroen Ooms <[email protected]> |
License: | GPL-2 | LGPL-2.1 | MPL-1.1 |
Version: | 3.0.5 |
Built: | 2024-12-02 05:59:17 UTC |
Source: | https://github.com/ropensci/hunspell |
The hunspell
function is a high-level wrapper for finding spelling
errors within a text document. It takes a character vector with text (plain
,
latex
, man
, html
or xml
format), parses out the words
and returns a list with incorrect words for each line. It effectively combines
hunspell_parse
with hunspell_check
in a single step.
Other functions in the package operate on individual words, see details.
hunspell( text, format = c("text", "man", "latex", "html", "xml"), dict = dictionary("en_US"), ignore = en_stats ) hunspell_parse( text, format = c("text", "man", "latex", "html", "xml"), dict = dictionary("en_US") ) hunspell_check(words, dict = dictionary("en_US")) hunspell_suggest(words, dict = dictionary("en_US")) hunspell_analyze(words, dict = dictionary("en_US")) hunspell_stem(words, dict = dictionary("en_US")) hunspell_info(dict = dictionary("en_US")) dictionary(lang = "en_US", affix = NULL, add_words = NULL, cache = TRUE) list_dictionaries()
hunspell( text, format = c("text", "man", "latex", "html", "xml"), dict = dictionary("en_US"), ignore = en_stats ) hunspell_parse( text, format = c("text", "man", "latex", "html", "xml"), dict = dictionary("en_US") ) hunspell_check(words, dict = dictionary("en_US")) hunspell_suggest(words, dict = dictionary("en_US")) hunspell_analyze(words, dict = dictionary("en_US")) hunspell_stem(words, dict = dictionary("en_US")) hunspell_info(dict = dictionary("en_US")) dictionary(lang = "en_US", affix = NULL, add_words = NULL, cache = TRUE) list_dictionaries()
text |
character vector with arbitrary input text |
format |
input format; supported parsers are |
dict |
a dictionary object or string which can be passed to |
ignore |
character vector with additional approved words added to the dictionary |
words |
character vector with individual words to spell check |
lang |
dictionary file or language, see details |
affix |
file path to corresponding affix file. If |
add_words |
a character vector of additional words to add to the dictionary |
cache |
speed up loading of dictionaries by caching |
Hunspell uses a special dictionary format that defines which stems and affixes are
valid in a given language. The hunspell_analyze
function shows how a
word breaks down into a valid stem plus affix. The hunspell_stem
function is similar but only returns valid stems for a given word. Stemming can be
used to summarize text (e.g in a wordcloud). The hunspell_check
function
takes a vector of individual words and tests each one for correctness. Finally
hunspell_suggest
is used to suggest correct alternatives for each
(incorrect) input word.
Because spell checking is usually done on a document, the package includes some
parsers to extract words from various common formats. With hunspell_parse
we can parse plain-text, latex and man format. R also has a few built-in parsers
such as RdTextFilter
and
SweaveTeXFilter
, see also
?aspell
.
The package searches for dictionaries in the working directory as well as in the
standard system locations. list_dictionaries
provides a list of all
dictionaries it can find. Additional search paths can be specified by setting
the DICPATH
environment variable. A US English dictionary (en_US
) is
included with the package; other dictionaries need to be installed by the system.
Most operating systems already include compatible dictionaries with names such as
hunspell-en-gb or
myspell-en-gb.
To manually install dictionaries, copy the corresponding .aff
and .dic
file to ~/Library/Spelling
or a custom directory specified in DICPATH
.
Alternatively you can pass the entire path to the .dic
file as the dict
parameter. Some popular sources of dictionaries are
SCOWL,
OpenOffice,
debian,
github/titoBouzout or
github/wooorm.
Note that hunspell
uses iconv
to convert input text to
the encoding used by the dictionary. This will fail if text
contains characters
which are unsupported by that particular encoding. For this reason UTF-8 dictionaries
are preferable over legacy 8-bit dictionaries.
# Check individual words words <- c("beer", "wiskey", "wine") correct <- hunspell_check(words) print(correct) # Find suggestions for incorrect words hunspell_suggest(words[!correct]) # Extract incorrect from a piece of text bad <- hunspell("spell checkers are not neccessairy for langauge ninja's") print(bad[[1]]) hunspell_suggest(bad[[1]]) # Stemming words <- c("love", "loving", "lovingly", "loved", "lover", "lovely", "love") hunspell_stem(words) hunspell_analyze(words) # Check an entire latex document tmpfile <- file.path(tempdir(), "1406.4806v1.tar.gz") download.file("https://arxiv.org/e-print/1406.4806v1", tmpfile, mode = "wb") untar(tmpfile, exdir = tempdir()) text <- readLines(file.path(tempdir(), "content.tex"), warn = FALSE) bad_words <- hunspell(text, format = "latex") sort(unique(unlist(bad_words))) # Summarize text by stems (e.g. for wordcloud) allwords <- hunspell_parse(text, format = "latex") stems <- unlist(hunspell_stem(unlist(allwords))) words <- head(sort(table(stems), decreasing = TRUE), 200)
# Check individual words words <- c("beer", "wiskey", "wine") correct <- hunspell_check(words) print(correct) # Find suggestions for incorrect words hunspell_suggest(words[!correct]) # Extract incorrect from a piece of text bad <- hunspell("spell checkers are not neccessairy for langauge ninja's") print(bad[[1]]) hunspell_suggest(bad[[1]]) # Stemming words <- c("love", "loving", "lovingly", "loved", "lover", "lovely", "love") hunspell_stem(words) hunspell_analyze(words) # Check an entire latex document tmpfile <- file.path(tempdir(), "1406.4806v1.tar.gz") download.file("https://arxiv.org/e-print/1406.4806v1", tmpfile, mode = "wb") untar(tmpfile, exdir = tempdir()) text <- readLines(file.path(tempdir(), "content.tex"), warn = FALSE) bad_words <- hunspell(text, format = "latex") sort(unique(unlist(bad_words))) # Summarize text by stems (e.g. for wordcloud) allwords <- hunspell_parse(text, format = "latex") stems <- unlist(hunspell_stem(unlist(allwords))) words <- head(sort(table(stems), decreasing = TRUE), 200)