CLASS-BASED NAMED ENTITY TRANSLATION IN A SPEECH TO SPEECH TRANSLATION SYSTEM

Named Entity (NE) Translation is a challenging problem in Machine Translation (MT). Most of the training bi-text corpora for MT lack enough samples of NEs to cover the wide variety of contexts NEs can appear in. In this paper, we present a technique to translate NEs based on their NE types in addition to a phrase-based translation model. Our NE translation model is based on a syntax-based system similar to [1]; but we produce syntax-based rules with non-terminals as NE types instead of general non-terminals. Such classbased rules allow us to better generalize the context NEs. We show that our proposed method obtains a relative improvement of 1.41 % in BLEU score over the baseline of phrasebased model in NE test set