Translation Model of Myanmar Phrases for Statistical Machine Translation

被引：0

作者：

Zin, Thet Thet ^{[1
]}

Soe, Khin Mar ^{[2
]}

Thein, Ni Lar ^{[1
]}

机构：

[1] Univ Comp Studies, Yangon, Myanmar

[2] Univ Comp Studies, Nat Language Proc Lab, Yangon, Myanmar

来源：

ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS: WITH ASPECTS OF ARTIFICIAL INTELLIGENCE | 2012年 / 6839卷

关键词：

Syntactic structure; Morphological analysis; Statistical machine translation; N-gram method; Bayes rule;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we present a translation model which uses syntactic structure and morphology of Myanmar language to improve Myanmar to English machine translation system. This system is implemented as a subsystem of Myanmar to English translation system and based on statistical approach by using Myanmar-English Bilingual corpus. It also uses two types of information: language model and translation model. The source language model is based on N-gram method to extract phrases from segmented Myanmar sentences and the translation model is based on syntactic structure, morphology of Myanmar language and Bayes rule to reformulate the translation probability. Experimental results showed that the proposed system gets a BLEU-score improvement of more than 22.08% in comparison with baseline SMT system.

引用

页码：235 / +

页数：2

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