A systematic comparison of various statistical alignment models
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Word reordering and a dynamic programming beam search algorithm for statistical machine translation
Computational Linguistics
The mathematics of statistical machine translation: parameter estimation
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Fast decoding and optimal decoding for machine translation
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Translating named entities using monolingual and bilingual resources
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Greedy decoding for statistical machine translation in almost linear time
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Statistical phrase-based translation
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Stochastic finite-state models for spoken language machine translation
NAACL-ANLP-EMTS '00 Proceedings of the 2000 NAACL-ANLP Workshop on Embedded machine translation systems - Volume 5
A phrase-based, joint probability model for statistical machine translation
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Learning formulation and transformation rules for multilingual named entities
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
FSA: an efficient and flexible C++ toolkit for finite state automata using on-demand computation
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Automatic evaluation of machine translation quality using n-gram co-occurrence statistics
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A Structure-Based Model for Chinese Organization Name Translation
ACM Transactions on Asian Language Information Processing (TALIP)
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
A joint model to identify and align bilingual named entities
Computational Linguistics
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We propose a phrase-based context-dependent joint probability model for Named Entity (NE) translation. Our proposed model consists of a lexical mapping model and a permutation model. Target phrases are generated by the context-dependent lexical mapping model, and word reordering is performed by the permutation model at the phrase level. We also present a two-step search to decode the best result from the models. Our proposed model is evaluated on the LDC Chinese-English NE translation corpus. The experiment results show that our proposed model is high effective for NE translation.