This tool is used to turn Turkish text written in ASCII characters, which do not include some letters of the Turkish alphabet, into correctly written text with the appropriate Turkish characters (such as ı, ş, and so forth). It can also do the opposite, turning Turkish input into ASCII text, for the purpose of processing.
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- Java Development Kit 8 or higher, Open JDK or Oracle JDK
- Maven
- Git
To check if you have a compatible version of Java installed, use the following command:
java -version
If you don't have a compatible version, you can download either Oracle JDK or OpenJDK
To check if you have Maven installed, use the following command:
mvn --version
To install Maven, you can follow the instructions here.
Install the latest version of Git.
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 Deasciifier will be created. Or you can use below link for exploring the code:
git clone https://github.com/starlangsoftware/TurkishDeasciifier.git
Steps for opening the cloned project:
- Start IDE
- Select File | Open from main menu
- Choose
Deasciifier/pom.xml
file - Select open as project option
- Couple of seconds, dependencies with Maven will be downloaded.
From IDE
After being done with the downloading and Maven indexing, select Build Project option from Build menu. After compilation process, user can run Deasciifier
.
From Console
Use below line to generate jar file:
mvn install
<dependency>
<groupId>io.github.starlangsoftware</groupId>
<artifactId>Deasciifier</artifactId>
<version>1.0.25</version>
</dependency>
Asciifier converts text to a format containing only ASCII letters. This can be instantiated and used as follows:
Asciifier asciifier = new SimpleAsciifier();
Sentence sentence = new Sentence("çocuk"");
Sentence asciified = asciifier.asciify(sentence);
System.out.println(asciified);
Output:
cocuk
Deasciifier converts text written with only ASCII letters to its correct form using corresponding letters in Turkish alphabet. There are two types of Deasciifier
:
-
SimpleDeasciifier
The instantiation can be done as follows:
FsmMorphologicalAnalyzer fsm = new FsmMorphologicalAnalyzer(); Deasciifier deasciifier = new SimpleDeasciifier(fsm);
-
NGramDeasciifier
-
To create an instance of this, both a
FsmMorphologicalAnalyzer
and aNGram
is required. -
FsmMorphologicalAnalyzer
can be instantiated as follows:FsmMorphologicalAnalyzer fsm = new FsmMorphologicalAnalyzer();
-
NGram
can be either trained from scratch or loaded from an existing model.-
Training from scratch:
Corpus corpus = new Corpus("corpus.txt"); NGram ngram = new NGram(corpus.getAllWordsAsArrayList(), 1); ngram.calculateNGramProbabilities(new LaplaceSmoothing());
There are many smoothing methods available. For other smoothing methods, check here.
-
Loading from an existing model:
NGram ngram = new NGram("ngram.txt"); ngram.calculateNGramProbabilities(new LaplaceSmoothing());
-
For further details, please check here.
-
Afterwards,
NGramDeasciifier
can be created as below:Deasciifier deasciifier = new NGramDeasciifier(fsm, ngram);
-
A text can be deasciified as follows:
Sentence sentence = new Sentence("cocuk");
Sentence deasciified = deasciifier.deasciify(sentence);
System.out.println(deasciified);
Output:
çocuk