Large Margin Classification Using the Perceptron Algorithm
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Maximum Entropy Markov Models for Information Extraction and Segmentation
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Computational Linguistics
An English-Korean transliteration model using pronunciation and contextual rules
COLING '02 Proceedings of the 19th international 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
Learning structured prediction models: a large margin approach
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Machine transliteration of names in Arabic text
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EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
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
A discriminative matching approach to word alignment
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
A discriminative framework for bilingual word alignment
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Named entity transliteration and discovery from multilingual comparable corpora
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Phoneme-Based transliteration of foreign names for OOV problem
IJCNLP'04 Proceedings of the First international joint conference on Natural Language Processing
Learning phoneme mappings for transliteration without parallel data
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Loss-sensitive discriminative training of machine transliteration models
SRWS '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Student Research Workshop and Doctoral Consortium
Discriminative substring decoding for transliteration
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
Report of NEWS 2009 machine transliteration shared task
NEWS '09 Proceedings of the 2009 Named Entities Workshop: Shared Task on Transliteration
Combining MDL transliteration training with discriminative modeling
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)
Report of NEWS 2010 transliteration generation shared task
NEWS '10 Proceedings of the 2010 Named Entities Workshop
Machine transliteration survey
ACM Computing Surveys (CSUR)
Machine transliteration: leveraging on third languages
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Leveraging supplemental representations for sequential transduction
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Report of NEWS 2012 machine transliteration shared task
NEWS '12 Proceedings of the 4th Named Entity Workshop
MDL-based models for transliteration generation
SLSP'13 Proceedings of the First international conference on Statistical Language and Speech Processing
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We present two discriminative methods for name transliteration. The methods correspond to local and global modeling approaches in modeling structured output spaces. Both methods do not require alignment of names in different languages -- their features are computed directly from the names themselves. We perform an experimental evaluation of the methods for name transliteration from three languages (Arabic, Korean, and Russian) into English, and compare the methods experimentally to a state-of-the-art joint probabilistic modeling approach. We find that the discriminative methods outperform probabilistic modeling, with the global discriminative modeling approach achieving the best performance in all languages.