A statistical approach to machine translation
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An ensemble of transliteration models for information retrieval
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Direct orthographical mapping for machine transliteration
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
A phonetic similarity model for automatic extraction of transliteration pairs
ACM Transactions on Asian Language Information Processing (TALIP)
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A comparison of different machine transliteration models
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NEWS '09 Proceedings of the 2009 Named Entities Workshop: Shared Task on Transliteration
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Information Sciences: an International Journal
Compositional Machine Transliteration
ACM Transactions on Asian Language Information Processing (TALIP)
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ACM Transactions on Asian Language Information Processing (TALIP)
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Report of NEWS 2010 transliteration generation shared task
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Machine transliteration survey
ACM Computing Surveys (CSUR)
Improving machine transliteration performance by using multiple transliteration models
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Improving back-transliteration by combining information sources
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Direct combination of spelling and pronunciation information for robust back-transliteration
CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
A phrase-based context-dependent joint probability model for named entity translation
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
Report of NEWS 2012 machine transliteration shared task
NEWS '12 Proceedings of the 4th Named Entity Workshop
A joint model to identify and align bilingual named entities
Computational Linguistics
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There is increasing concern about English-Korean (E-K) transliteration recently. In the previous works, direct converting methods from English alphabets to Korean alphabets were a main research topic. In this paper, we present an E-K transliteration model using pronunciation and contextual rules. Unlike the previous works, our method uses phonetic information such as phoneme and its context. We also use word formation information such as English words of Greek origin, With them, our method shows significant performance increase about 31% in word accuracy.