JamSpell
SymSpell
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JamSpell | SymSpell | |
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3 | 1 | |
590 | 9 | |
- | - | |
2.4 | 0.0 | |
6 months ago | about 10 years ago | |
C++ | JavaScript | |
MIT License | - |
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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 GNU aspell (that at one point was superseded by Hunspell, but still holds its ground in English suggestion quality), to name one of the older ones; but also there are novel approaches, like SymSpell,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.
SymSpell
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Rebuilding the spellchecker, pt.3: Lookup–compounds and solutions
For what I know (I've mentioned it in the first part[0]), the nspell[1] is the most close to "port (some) of Hunspell", and typo.js[2] ports even less (but might be enough for some, we used it in my previous company: it uses dictionaries for lookup, but uses its own simplistic suggest, which I needed to tweak a lot).
SymSpell algorithm (which is quite different, I'll go into it in the next part to some extent) is much easier to port, so there is a JS SymSpell port[3] (which seems abandoned though).
0: https://zverok.github.io/blog/2021-01-05-spellchecker-1.html
1: https://github.com/wooorm/nspell
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.
languagetool - Style and Grammar Checker for 25+ Languages
WeCantSpell.Hunspell - A port of Hunspell v1 for .NET and .NET Standard
goSpellcheck - A terrible spell checker in Go.
ruby-spellchecker - Fast English spelling and grammar checker that can be used for autocorrection.
spylls - Pure Python spell-checker, (almost) full port of Hunspell
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.