Translating unknown words using WordNet and IPA-based-transliteration

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...

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Bibliographic Details
Main Authors: Salam, K. M. A., Setsuo, Y., Nishino, T.
Format: Conference Proceeding
Language:English
Subjects:
Dictionaries
Example-Based Machine Translation
Gold
Indexes
Machine Translation
Marine vehicles
Software
Transliteration
WordNet
Online Access:Request full text
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Summary: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. For proper nouns, the system uses Akkhor transliteration mechanism. We implemented the proposed approach in EBMT, which improved the quality of good translation by 16 points.
DOI:10.1109/ICCITechn.2011.6164838