Hello, The goal of this project was to identify LPD possible in sentences for hebrew

for example: "היה לי לוחם ממש טוב" <=> "היה לי חלום ממש טוב", "רוצה לבוא לאכול גדילה" <=> "רוצה לבוא לאכול גלידה"

In this project has several parts:

I downloaded form Mila site : http://www.mila.cs.technion.ac.il/resources_corpora_wikipedia_2013.html Corpus for wikpdia 2013, And extracted as many sentences as I could (more 192000000 sentences) It was not simple (prepareTheCorpus.py)

The next step was to create a vocabulary, a Bigram model and I test sentences with LPD the test sentence is not import to train courps.

the baseLine is simple: For each word I choose a random combinator, that exists in a dictionary. of all possible combinations. The results were really bad: 0% Almost all the words in the sentence were changed and no sentence came out as the desired sentence.

For each word I choose a the word that appeared most often. The results were a bit nicer: 64%

For each word I choose the word that its probability when known as the previous word and the next word is the highest. The results in this case were really impressive:97%

for play yourself run test model bigram.

1. You can enter any sentence you want and test it.
2. You can choose a sentence between the test corpus.
3. You can select a sentence that has an error from the test corpus. (It helped me check the errors, and improve the results)

Thanks