Algorithms for Arabic name transliteration
IBM Journal of Research and Development
Statistical transliteration for english-arabic cross language information retrieval
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Computational Linguistics
An English to Korean transliteration model of extended Markov window
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Translating named entities using monolingual and bilingual resources
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Machine transliteration of names in Arabic text
SEMITIC '02 Proceedings of the ACL-02 workshop on Computational approaches to semitic languages
Transliteration of proper names in cross-lingual information retrieval
MultiNER '03 Proceedings of the ACL 2003 workshop on Multilingual and mixed-language named entity recognition - Volume 15
A joint source-channel model for machine transliteration
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Named entity translation: extended abstract
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Translating names and technical terms in Arabic text
Semitic '98 Proceedings of the Workshop on Computational Approaches to Semitic Languages
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Automated mining of names using parallel Hindi-English corpus
ALR7 Proceedings of the 7th Workshop on Asian Language Resources
Learning multi character alignment rules and classification of training data for transliteration
NEWS '09 Proceedings of the 2009 Named Entities Workshop: Shared Task on Transliteration
NEWS '09 Proceedings of the 2009 Named Entities Workshop: Shared Task on Transliteration
English to Hindi machine transliteration system at NEWS 2009
NEWS '09 Proceedings of the 2009 Named Entities Workshop: Shared Task on Transliteration
Transliteration for Resource-Scarce Languages
ACM Transactions on Asian Language Information Processing (TALIP)
Hindi-to-Urdu machine translation through transliteration
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
English to Indian languages machine transliteration system at NEWS 2010
NEWS '10 Proceedings of the 2010 Named Entities Workshop
Machine transliteration survey
ACM Computing Surveys (CSUR)
MDL-based models for transliteration generation
SLSP'13 Proceedings of the First international conference on Statistical Language and Speech Processing
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Most machine transliteration systems transliterate out of vocabulary (OOV) words through intermediate phonemic mapping. A framework has been presented that allows direct orthographical mapping between two languages that are of different origins employing different alphabet sets. A modified joint source-channel model along with a number of alternatives have been proposed. Aligned transliteration units along with their context are automatically derived from a bilingual training corpus to generate the collocational statistics. The transliteration units in Bengali words take the pattern C+M where C represents a vowel or a consonant or a conjunct and M represents the vowel modifier or matra. The English transliteration units are of the form C*V* where C represents a consonant and V represents a vowel. A Bengali-English machine transliteration system has been developed based on the proposed models. The system has been trained to transliterate person names from Bengali to English. It uses the linguistic knowledge of possible conjuncts and diphthongs in Bengali and their equivalents in English. The system has been evaluated and it has been observed that the modified joint source-channel model performs best with a Word Agreement Ratio of 69.3% and a Transliteration Unit Agreement Ratio of 89.8%.