https://github.com/Wavesonics/SymSpellKt
A Kotlin Multiplatform implementation of the SymSpell algorithm.
https://github.com/Wavesonics/SymSpellKt
kotlin kotlin-multiplatform spellcheck spelling spelling-correction
Last synced: about 1 month ago
JSON representation
A Kotlin Multiplatform implementation of the SymSpell algorithm.
- Host: GitHub
- URL: https://github.com/Wavesonics/SymSpellKt
- Owner: Wavesonics
- License: mit
- Created: 2024-02-05T01:59:06.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-27T08:31:12.000Z (about 2 months ago)
- Last Synced: 2025-03-27T09:38:24.851Z (about 2 months ago)
- Topics: kotlin, kotlin-multiplatform, spellcheck, spelling, spelling-correction
- Language: Kotlin
- Homepage:
- Size: 13.6 MB
- Stars: 49
- Watchers: 2
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-list - Wavesonics/SymSpellKt - A Kotlin Multiplatform implementation of the SymSpell algorithm. (Kotlin)
README
# SymSpell Spell Check Kotlin
[](https://search.maven.org/artifact/com.darkrockstudios/symspellkt)
[](http://kotlinlang.org)
[](http://kotlinlang.org)
![badge-jvm] ![badge-android] ![badge-wasm] ![badge-wasmi] ![badge-jsir] ![badge-linux] ![badge-windows] ![badge-mac-x86] ![badge-mac-arm]
![badge-ios] ![badge-ios-sim]
_This is a Kotlin Multiplatform implementation of the [symspell](https://github.com/wolfgarbe/symspell) fuzzy search
algorithm. It has been ported from this [Java implementation](https://github.com/MighTguY/customized-symspell/) of symspell._
## Dependency
`implementation("com.darkrockstudios:symspellkt:3.3.0")`
## Sample
Try out the sample desktop application:
`gradlew sampleCompose:run`
[Try sample here](https://wavesonics.github.io/SymSpellKt/)
[](https://wavesonics.github.io/SymSpellKt/)
## SymSpell v6.6 (Bigrams)
* the optional bigram dictionary in order to use sentence level context information for selecting best spelling
correction.
## SymSpell
* The Symmetric Delete spelling correction algorithm reduces the complexity of edit candidate generation and dictionary
lookup for a given Damerau-Levenshtein distance.
* It is six orders of magnitude faster (than the standard approach with deletes + transposes + replaces + inserts) and
language independent.
* Opposite to other algorithms only deletes are required, no transposes + replaces + inserts. Transposes + replaces +
inserts of the input term are transformed into deletes of the dictionary term.
* The speed comes from the inexpensive delete-only edit candidate generation and the pre-calculation.
## Fdic: Binary Frequency Dictionary file format
In order to optimize for size on disk, and speed of loading and parsing, I made a little file format to encode the
common plain text frequency dictionaries use with SymSpell style spell checkers.
[fdic](Fdic/README.md) is both smaller on disk, and faster to load than either plain text or gzipped dictionaries. In some cases being:
- 70% faster to load and parse
- More than 40% smaller on disk.
There is a [CLI program](FdicCli/README.md) for producing `.fdic` files from a standard plain text frequency dictionary, as well as some
extension functions in an [addon library](SymSpellKtFdic/README.md) for loading them into a SymSpellKt SpellChecker object.
[badge-android]: http://img.shields.io/badge/-android-6EDB8D.svg?style=flat
[badge-jvm]: http://img.shields.io/badge/-jvm-DB413D.svg?style=flat
[badge-js]: http://img.shields.io/badge/-js-F8DB5D.svg?style=flat
[badge-js-ir]: https://img.shields.io/badge/support-[IR]-AAC4E0.svg?style=flat
[badge-linux]: http://img.shields.io/badge/-linux-2D3F6C.svg?style=flat
[badge-windows]: http://img.shields.io/badge/-windows-4D76CD.svg?style=flat
[badge-wasm]: https://img.shields.io/badge/-wasm-624FE8.svg?style=flat
[badge-wasmi]: https://img.shields.io/badge/-wasi-626FFF.svg?style=flat
[badge-jsir]: https://img.shields.io/badge/-js(IR)-22D655.svg?style=flat
[badge-apple-silicon]: http://img.shields.io/badge/support-[AppleSilicon]-43BBFF.svg?style=flat
[badge-ios]: http://img.shields.io/badge/-ios-CDCDCD.svg?style=flat
[badge-ios-sim]: http://img.shields.io/badge/-iosSim-AFAFAF.svg?style=flat
[badge-mac-arm]: http://img.shields.io/badge/-macosArm-444444.svg?style=flat
[badge-mac-x86]: http://img.shields.io/badge/-macosX86-111111.svg?style=flat
[badge-watchos]: http://img.shields.io/badge/-watchos-C0C0C0.svg?style=flat
[badge-tvos]: http://img.shields.io/badge/-tvos-808080.svg?style=flat