Aligning Turkish and English Parallel Texts for Statistical Machine Translation

摘要

This paper presents a preliminary work on aligning Turkish and English parallel texts towards developing a statistical machine translation system for English and Turkish. To avoid the data sparse-ness problem and to uncover relations between sublexical components of words such as morphemes, we have converted our parallel texts to a morphemic representation and then used standard word alignment algorithms. Results from a mere 3K sentences of parallel English-Turkish texts show that we are able to link Turkish morphemes with English morphemes and function words quite successfully. We have also used the Turkish WordNet which is linked with the English WordNet, as a bootstrapping dictionary to constrain root word alignments.