presented in 3rd regional conference on new achievements in electrical and computer engineering

1. Improvement of English to Persian
Machine Translation via N-grams of
Part-of-Speech tags
Adel Rahimi
Sharif University Of Technlogy
adel.rahimi@mehr.sharif.edu
3rd Regional Conference On New Achievements In Electrical And Computer Engineering

2. Hi! I’m Adel Rahimi
I work at Sharif Speech and Language
Processing Lab.
I love NLP and Data Mining.
You can find me at:
http://mehr.sharif.edu/~adel.rahimi
Adel.rahimi@mehr.sharif.edu
2

3. IN SHORT Machine Translation has always been an interesting topic in
the NLP.
It’s always improving, we tried a new method to align the
English to Persian machine-translated texts. We used n-gram
modelling for part-of-speech tagged tokens. This method
improved the accuracy for syntactical mistranslated sentences.
3

4. PREVIOUS
STUDIES
▫Orch (1999) used a method that translated word by
word and then reordered words as the destination
language’s syntactic structure
▫Koehn (2009) proposed that we translate phrases
regardless of word structures
▫Kumar & Byrne (2008), Blackwell (2006), and
Kumar (2003) all were looking for a method to use
Finite State Transducer
4

5. HOW WAS IT DONE?

6. METHODOLOGY We used N-gram of POS tagged items:
‫من‬‫این‬‫کد‬‫من‬ ‫و‬‫میخواهم‬
pronoun pronoun noun conjunction pronoun verb
‫من‬‫خواهم‬‫رفت‬
pronoun verb
6

7. THE DATASET
7
String
n n pro spec
n n pro qua spec n
n p n p v adv
n pro p adv v pro
p n adj adj n
number
۱
۲
۳
۴
۵

8. 8
HOW ABOUT THE ACCURACY?

9. 9
‫فارسی‬ ‫اصلی‬ ‫ی‬‫جمله‬‫یک‬ ‫این‬‫متریک‬‫است‬ ‫متداول‬ ‫بسیار‬
‫انگلیسی‬ ‫اصلی‬ ‫ی‬‫جمله‬This is a very common meteric
‫شده‬ ‫ترجمه‬ ‫ی‬‫جمله‬‫است‬ ‫متداول‬ ‫بسیار‬ ‫این‬ ‫متریک‬ ‫یک‬
‫شده‬‫ترجمه‬ ‫کالم‬ ‫اجزای‬ ‫ی‬‫دنباله‬n n pro adj adj v
‫ی‬‫دنباله‬‫شده‬ ‫اصالح‬ ‫کالم‬ ‫اجزای‬pro n n adj adj v

10. 10
65 percent accuracy

11. 11
THANKS Any questions?
Contact me at:
▫ Mehr.sharif.edu/~adel.rahimi
▫ Adel.rahimi@mehr.sharif.edu