Abstract
Due to small available English-Bangla parallel corpus, Example-Based Machine Translation (EBMT) system has high probability of handling unknown words. To improve translation quality for Bangla language, we propose a novel approach for EBMT using WordNet and International-Phonetic-Alphabet(IPA)-based transliteration. Proposed system first tries to find semantically related English words from WordNet for the unknown word. From these related words, we choose the semantically closest related word whose Bangla translation exists in English-Bangla dictionary. If no Bangla translation exists, the system uses IPA-based-transliteration. If unknown word is not found in the English IPA dictionary, the system uses Akkhor transliteration mechanism. We implemented the proposed approach in EBMT, which improved the quality of good translation by 16 points.
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