Extracting Persian-English Parallel Sentences from DocumentLevel Aligned Comparable Corpus using Bi-DirectionalTranslation

Bilingual parallel corpora are very important in variousfiled of natural language processing (NLP). The quality of aStatistical Machine Translation (SMT) system stronglydependent upon the amount of training data. For low resourcelanguage pairs such as Persian-English, there are not enoughparallel sentences to build an accurate SMT system. This paperdescribes a new approach to use the Wikipedia as a comparablecorpus to extract Persian-English parallel sentences andeventually improve SMT system performance. This newapproach is also applicable to other low resource language pairs.In order to calculate the similarity score between two sentences, anovel bi-directional translation-based information retrievalsystem is proposed. A length penalty score is introduced toincrease the accuracy of extracted corpus. Using extractedparallel sentences, the performance of existing Persian-EnglishSMT is improved drastically

کلیدواژه ها:

comparable corpus ، bi-directional translation ، statistical machine translation ، Wikipedia ، information retrieval