Rapid integration of parts of speech information to improve reordering model for english-Farsi speech to speech translation

Integrating Parts of Speech (POS) information to Machine Translation (MT) model usually amounts to significant changes in the MT decoder. We present a method to rapidly integrate POS information without adding complexity to the decoder. We show how we can re-estimate the lexicalized reordering probability estimates with POS tags during the training time without having to use POS tagger at the decoding phase. We present our empirical results for two different MT decoding algorithms that use lexicalized reordering models. ©2010 IEEE.