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Using TectoMT as a Preprocessing Tool for Phrase-Based Statistical Machine Translation

Publication at Faculty of Mathematics and Physics |
2010

Abstract

We present a systematic comparison of preprocessing techniques for two language pairs: English-Czech and English-Hindi. The two target languages, although both belonging to the Indo-European language family, show significant differences in morphology, syntax and word order.

We describe how TectoMT, a successful framework for analysis and generation of language, can be used as preprocessor for a phrase-based MT system. We compare the two language pairs and the optimal sets of source-language transformations applied to them.

The following transformations are examples of possible preprocessing steps: lemmatization; retokenization, compound splitting; removing/adding words lacking counterparts in the other language; phrase reordering to resemble the target word order; marking syntactic functions. TectoMT, as well as all other tools and data sets we use, are freely available on the Web.