A maximum entropy approach to natural language processing
Computational Linguistics
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Ultraconservative online algorithms for multiclass problems
The Journal of Machine Learning Research
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
A joint source-channel model for machine transliteration
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
A generic framework for machine transliteration
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
A comparison of different machine transliteration models
Journal of Artificial Intelligence Research
Report of NEWS 2009 machine transliteration shared task
NEWS '09 Proceedings of the 2009 Named Entities Workshop: Shared Task on Transliteration
Whitepaper of NEWS 2009 machine transliteration shared task
NEWS '09 Proceedings of the 2009 Named Entities Workshop: Shared Task on Transliteration
Report of NEWS 2009 machine transliteration shared task
NEWS '09 Proceedings of the 2009 Named Entities Workshop: Shared Task on Transliteration
Compositional Machine Transliteration
ACM Transactions on Asian Language Information Processing (TALIP)
Reranking with multiple features for better transliteration
NEWS '10 Proceedings of the 2010 Named Entities Workshop
Machine transliteration: leveraging on third languages
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
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This paper describes our approach to "NEWS 2009 Machine Transliteration Shared Task." We built multiple transliteration engines based on different combinations of two transliteration models and three machine learning algorithms. Then, the outputs from these transliteration engines were combined using re-ranking functions. Our method was applied to all language pairs in "NEWS 2009 Machine Transliteration Shared Task." The official results of our standard runs were ranked the best for four language pairs and the second best for three language pairs.