JamSpell
WeCantSpell.Hunspell
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JamSpell | WeCantSpell.Hunspell | |
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3 | 1 | |
591 | 115 | |
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2.4 | 0.0 | |
7 months ago | 4 months ago | |
C++ | C# | |
MIT License | GNU General Public License v3.0 or later |
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JamSpell
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Rebuilding the spellchecker, pt.4: Introduction to suggest algorithm
There is, for example, a curious evaluation table provided by a modern ML-based spellchecker JamSpell. According to it, JamSpell is awesome—while Hunspell is a mere 0.03% better than dummy ("fix nothing") spellchecker... Which doesn't ring true, somehow!
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Rebuilding the spellchecker, pt.3: Lookup–compounds and solutions
That's a huge topic, which I am planning to cover towards the end of the article series please like and subscribe, but in short: yes, my opinion is that spellchecking is actually a "machine learning problem in disguise", and most of existing dictionaries are more a roundabout way of storing something-not-unlike-models than analytical data.
But ML approach will raise a question of data availability. What good your "deep learning OSS spellchecker" will do if there aren't good (and open) models for it which cover as much languages as existing Hunspell dictionaries do? And what if adding a bunch of new words requires laborous model retraining? It is not unsolvable, but non-trivial.
I believe all the giants have something like this inside (I don't think spelling correction in Google search bar is handled with Hunspell, right?), but it is much harder to do as an open tool, ready to embedding into other software.
There are a notable attempts, though: JamSpell for one (https://github.com/bakwc/JamSpell), which has an open "free" models, and more precise commercial ones; source code is open (maybe also only for using "simplistic" models, haven't dug deeper).
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Rebuilding the most popular spellchecker. Part 1
Obviously, there are open-source spellcheckers other than Hunspell. GNU aspell (that at one point was superseded by Hunspell, but still holds its ground in English suggestion quality), to name one of the older ones; but also there are novel approaches, like SymSpell, claiming to be "1 million times faster" or ML-based JamSpell, claiming to be much more accurate.
WeCantSpell.Hunspell
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Rebuilding the most popular spellchecker. Part 1
Note that there are also a few "pragmatic" ports of Hunspell into other languages (in order to use it in environments where C++ dependency is undesireable), namely WeCantSpell.Hunspell in C# and nspell in JS (very incomplete); and aforementioned nuspell can also be considered a "port" (from legacy C++ to a modern one).
What are some alternatives?
SymSpell - SymSpell: 1 million times faster spelling correction & fuzzy search through Symmetric Delete spelling correction algorithm
hunspell - The most popular spellchecking library.
SymSpell - A JavaScript implementation of the Symmetric Delete spelling correction algorithm.
spylls - Pure Python spell-checker, (almost) full port of Hunspell
NetSpell - Spell Checker for .NET
ruby-spellchecker - Fast English spelling and grammar checker that can be used for autocorrection.
goSpellcheck - A terrible spell checker in Go.
languagetool - Style and Grammar Checker for 25+ Languages
mini_phone - A fast phone number parser, validator and formatter for Ruby. This gem binds to Google's C++ libphonenumber for spec-compliance and performance.
liquid-cpp - A C++ liquid parser/renderer, with an eye on embeddability, performance, extensibility, sandboxability, and multi-language interop.