A maximum entropy approach to natural language processing
Computational Linguistics
The TREC-5 Confusion Track: Comparing Retrieval Methods for Scanned Text
Information Retrieval
Automatic English-Chinese name transliteration for development of multilingual resources
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Translating named entities using monolingual and bilingual resources
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
HLT-NAACL-PARALLEL '03 Proceedings of the HLT-NAACL 2003 Workshop on Building and using parallel texts: data driven machine translation and beyond - Volume 3
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
Punjabi machine transliteration
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Unsupervised constraint driven learning for transliteration discovery
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
A comparison of different machine transliteration models
Journal of Artificial Intelligence Research
Named entity translation with web mining and transliteration
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Whitepaper of NEWS 2009 machine transliteration shared task
NEWS '09 Proceedings of the 2009 Named Entities Workshop: Shared Task on Transliteration
Phoneme-Based transliteration of foreign names for OOV problem
IJCNLP'04 Proceedings of the First international joint conference on Natural Language Processing
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Inspired by the success of English grapheme-to-phoneme research in speech synthesis, many researchers have proposed phoneme-based English-to-Chinese transliteration models. However, such approaches have severely suffered from the errors in Chinese phoneme-to-grapheme conversion. To address this issue, we propose a new English-to-Chinese transliteration model and make systematic comparisons with the conventional models. Our proposed model relies on the joint use of Chinese phonemes and their corresponding English graphemes and phonemes. Experiments showed that Chinese phonemes in our proposed model can contribute to the performance improvement in English-to-Chinese transliteration.