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.

Simple Web Interface

Link 1 Link 2

Video Lectures

For Developers

You can also see Java, Python, Cython, C++, C, Js, or C# repository.

Requirements

• Xcode Editor
• Git

Git

Install the latest version of Git.

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 TurkishSpellChecker-Swift will be created. Or you can use below link for exploring the code:

git clone https://github.com/starlangsoftware/TurkishSpellChecker-Swift.git

Open project with XCode

To import projects from Git with version control:

• XCode IDE, select Clone an Existing Project.

• In the Import window, paste github URL.

• Click Clone.

Result: The imported project is listed in the Project Explorer view and files are loaded.

Compile

From IDE

After being done with the downloading and opening project, select Build option from Product menu. After compilation process, user can run TurkishSpellChecker-Swift.

For Developers

• Creating SpellChecker
• 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.

      let fsm = FsmMorphologicalAnalyzer()
      let spellChecker = SimpleSpellChecker(fsm);  
    

• NGramSpellChecker,

  • To create an instance of this, both a FsmMorphologicalAnalyzer and a NGram is required.

  • FsmMorphologicalAnalyzer can be instantiated as follows:

      let fsm = FsmMorphologicalAnalyzer()
    

  • NGram can be either trained from scratch or loaded from an existing model.

    • Training from scratch:

        let corpus = Corpus("corpus.txt")
        let ngram = NGram(corpus.getAllWordsAsArrayList(), 1)
        ngram.calculateNGramProbabilities(LaplaceSmoothing())
      

    There are many smoothing methods available. For other smoothing methods, check here.

    • Loading from an existing model:

        let ngram = NGram("ngram.txt")
      

  For further details, please check here.

  • Afterwards, NGramSpellChecker can be created as below:

      let spellChecker = NGramSpellChecker(fsm, ngram)
    

Spell Correction

Spell correction can be done as follows:

let sentence = Sentence("Dıktor olaç yazdı")
let corrected = spellChecker.spellCheck(sentence)

Output:

Doktor ilaç yazdı

For Contibutors

Package.swift file

1. Dependencies should be given w.r.t github.

    dependencies: [
        .package(name: "MorphologicalAnalysis", url: "https://github.com/StarlangSoftware/TurkishMorphologicalAnalysis-Swift.git", .exact("1.0.6"))],

2. Targets should include direct dependencies, files to be excluded, and all resources.

    targets: [
        .target(
	dependencies: ["MorphologicalAnalysis"],
	exclude: ["turkish1944_dictionary.txt", "turkish1944_wordnet.xml",
	"turkish1955_dictionary.txt", "turkish1955_wordnet.xml",
	"turkish1959_dictionary.txt", "turkish1959_wordnet.xml",
	"turkish1966_dictionary.txt", "turkish1966_wordnet.xml",
	"turkish1969_dictionary.txt", "turkish1969_wordnet.xml",
	"turkish1974_dictionary.txt", "turkish1974_wordnet.xml",
	"turkish1983_dictionary.txt", "turkish1983_wordnet.xml",
	"turkish1988_dictionary.txt", "turkish1988_wordnet.xml",
	"turkish1998_dictionary.txt", "turkish1998_wordnet.xml"],
	resources:
[.process("turkish_wordnet.xml"),.process("english_wordnet_version_31.xml"),.process("english_exception.xml")]),

3. Test targets should include test directory.

	.testTarget(
		name: "WordNetTests",
		dependencies: ["WordNet"]),

Data files

1. Add data files to the project folder.

Swift files

1. Do not forget to comment each function.

   /**
     * Returns the value to which the specified key is mapped.
     - Parameters:
        - id: String id of a key
     - Returns: value of the specified key
     */
    public func singleMap(id: String) -> String{
        return map[id]!
    }

2. Do not forget to define classes as open in order to be able to extend them in other packages.

	open class Word : Comparable, Equatable, Hashable

3. Function names should follow caml case.

	public func map(id: String)->String?

4. Write getter and setter methods.

	public func getSynSetId() -> String{
	public func setOrigin(origin: String){

5. Use separate test class extending XCTestCase for testing purposes.

final class WordNetTest: XCTestCase {
    var turkish : WordNet = WordNet()
    
    func testSize() {
        XCTAssertEqual(78326, turkish.size())
    }

6. Enumerated types should be declared as enum.

public enum CategoryType : String{
    case MATHEMATICS
    case SPORT
    case MUSIC

7. Implement == operator and hasher method for hashing purposes.

    public func hash(into hasher: inout Hasher) {
        hasher.combine(name)
    }
    public static func == (lhs: Relation, rhs: Relation) -> Bool {
        return lhs.name == rhs.name
    }

8. Make classes Comparable for comparison, Equatable for equality, and Hashable for hashing check.

	open class Word : Comparable, Equatable, Hashable

9. Implement < operator for comparison purposes.

    public static func < (lhs: Word, rhs: Word) -> Bool {
        return lhs.name < rhs.name
    }

10. Implement description for toString method.

	open func description() -> String{

11. Use Bundle and XMLParserDelegate for parsing Xml files.

	let url = Bundle.module.url(forResource: fileName, withExtension: "xml")
	var parser : XMLParser = XMLParser(contentsOf: url!)!
	parser.delegate = self
	parser.parse()

also use parser method.

public func parser(_ parser: XMLParser, didStartElement elementName: String, namespaceURI: String?, qualifiedName qName: String?, attributes attributeDict: [String : String])