Turkish Spell Checker
============
This tool is a spelling checker for Modern Turkish. It detects spelling errors and corrects them appropriately, through its list of misspellings and matching to the Turkish dictionary.
Video Lectures
============
[<img src="https://github.com/StarlangSoftware/TurkishSpellChecker/blob/master/video.jpg" width="50%">](https://youtu.be/wKwTKv6Jlo0)
For Developers
============
You can also see [Cython](https://github.com/starlangsoftware/TurkishSpellChecker-Cy), [Java](https://github.com/starlangsoftware/TurkishSpellChecker), [C++](https://github.com/starlangsoftware/TurkishSpellChecker-CPP), [Swift](https://github.com/starlangsoftware/TurkishSpellChecker-Swift), [Js](https://github.com/starlangsoftware/TurkishSpellChecker-Js), or [C#](https://github.com/starlangsoftware/TurkishSpellChecker-CS) repository.
## Requirements
* [Python 3.7 or higher](#python)
* [Git](#git)
### Python
To check if you have a compatible version of Python installed, use the following command:
python -V
You can find the latest version of Python [here](https://www.python.org/downloads/).
### Git
Install the [latest version of Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git).
## Pip Install
pip3 install NlpToolkit-SpellChecker
## Download Code
In order to work on code, create a fork from GitHub page.
Use Git for cloning the code to your local or below line for Ubuntu:
git clone <your-fork-git-link>
A directory called SpellChecker will be created. Or you can use below link for exploring the code:
git clone https://github.com/starlangsoftware/TurkishSpellChecker-Py.git
## Open project with Pycharm IDE
Steps for opening the cloned project:
* Start IDE
* Select **File | Open** from main menu
* Choose `DataStructure-PY` file
* Select open as project option
* Couple of seconds, project will be downloaded.
Detailed Description
============
+ [Creating SpellChecker](#creating-spellchecker)
+ [Spell Correction](#spell-correction)
## Creating SpellChecker
SpellChecker finds spelling errors and corrects them in Turkish. There are two types of spell checker available:
* `SimpleSpellChecker`
* To instantiate this, a `FsmMorphologicalAnalyzer` is needed.
fsm = FsmMorphologicalAnalyzer()
spellChecker = SimpleSpellChecker(fsm)
* `NGramSpellChecker`,
* To create an instance of this, both a `FsmMorphologicalAnalyzer` and a `NGram` is required.
* `FsmMorphologicalAnalyzer` can be instantiated as follows:
fsm = FsmMorphologicalAnalyzer()
* `NGram` can be either trained from scratch or loaded from an existing model.
* Training from scratch:
corpus = Corpus("corpus.txt");
ngram = NGram(corpus.getAllWordsAsArrayList(), 1)
ngram.calculateNGramProbabilities(LaplaceSmoothing())
*There are many smoothing methods available. For other smoothing methods, check [here](https://github.com/olcaytaner/NGram).*
* Loading from an existing model:
ngram = NGram("ngram.txt")
*For further details, please check [here](https://github.com/starlangsoftware/NGram).*
* Afterwards, `NGramSpellChecker` can be created as below:
spellChecker = NGramSpellChecker(fsm, ngram)
## Spell Correction
Spell correction can be done as follows:
sentence = Sentence("Dıktor olaç yazdı")
corrected = spellChecker.spellCheck(sentence)
print(corrected)
Output:
Doktor ilaç yazdı
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