Estimating Word Translation Probabilities for Thai – English Machine Translation using EM Algorithm
Selecting the word translation from a set of target
language words, one that conveys the correct sense of source word
and makes more fluent target language output, is one of core
problems in machine translation. In this paper we compare the 3
methods of estimating word translation probabilities for selecting the
translation word in Thai – English Machine Translation. The 3
methods are (1) Method based on frequency of word translation, (2)
Method based on collocation of word translation, and (3) Method
based on Expectation Maximization (EM) algorithm. For evaluation
we used Thai – English parallel sentences generated by NECTEC.
The method based on EM algorithm is the best method in comparison
to the other methods and gives the satisfying results.