Abstract
To develop a system for translation of one language to another is one of the most important research challenges in Artificial Intelligence (AI). In Machine Translation (MT) the name entity recognition (NER) is one of the most challenging task. In this paper we propose a new statistical method for transliterating the identified name entities based on the linguistic knowledge of possible conjuncts and diphthongs in source and target language. The work presented in this paper is part of a larger effort to develop MT system which can take care of name entities.
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References
Nasreen, A.J., Larkey, L.S.,: Statistical Transliteration for English-Arabic Cross Language Information Retrieval. In: Proceedings of the Twelfth International Conference on Information and Knowledge Management (CIKM 2003), New Orleans, USA, 139–146.(2003)
Al-Onaizan Y. and Knight K.: Named Entity Translation: Extended Abstract. Proceedings of the Human Language Technology Conference (HLT 2002), 122–124 (2002)
Al-Onaizan, Y. and Knight, K.: Translating Named Entities Using Monolingual and Bilingual Resources. Proceedings of the 40th Annual Meeting of the ACL (ACL 2002), 400–408 (2002).
Al-Onaizan, Y., Knight, K.: Machine Transliteration of Names in Arabic Text. Proceedings of the ACL Workshop on Computational Approaches to Semitic Languages (2002)
McCallum, A., Li, W.: Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons. In CoNLL (2003)
Arbabi, M., Scott, M., Fischthal, V., Cheng C., Bar E.: Algorithms for Arabic name transliteration. IBM Journal of Research and Development, 38(2), 183–193. (1994)
Ekbal, A., Naskar, S.K., Bandopadhaya, S.: A modified joint source-channel model for transliteration. Proceedings of the COLING/ACL on Main conference poster sessions. Sydney, Australia. pp: 191–198 (2006)
Crego J.M., Marino J.B., de Gispert, A.: Reordered Search and Tuple Unfolding for Ngrambased SMT. Proceedings of the MT-Summit X, Phuket, Thailand, 283–289 (2005)
Bikel D. M., Schwartz R. L., Weischedel R. M.: An algorithm that learns what’s in a name. Machine Learning, 34, 211–231 (1999)
Freitag, D: Information extraction from html: application of a general machine learning approach. In AAAI-98 (1998)
Goto I., Kato, N., Uratani, N., Ehara T.: Transliteration considering Context Information based on the Maximum Entropy Method. Proceedings of the MT-Summit IX, New Orleans, USA, 125–132 (2003)
Grishman, R.: Information Extraction: Techniques and Challenges”, Lecture Notes in Computer Science, Vol. 1299, Springer-Verlag (1997)
Li, H., Min, Z. Jian, S.: A Joint Source-Channel Model for Machine Transliteration. Proceedings of the 42nd Annual Meeting of the ACL (ACL 2004), Barcelona, Spain, 159–166 (2004)
Young, J. S., Hong S. L., Paek, E., An English to Korean Transliteration Model of Extended Markov Window. Proceedings of COLING 2000, 1, 383–389 (2000)
Knight K., Graehl, J.: Machine Transliteration, Computational Linguistics, 24(4), 599–612 (1998)
Marino J. B., Banchs R., Crego J. M., A. de Gispert, P. Lambert, J. A. Fonollosa and M. Ruiz, Bilingual N-gram Statistical Machine Translation. Proceedings of the MT-Summit X, Phuket, Thailand, 275–282.
Craven M., Kumlien, J.: Constructing biological knowledge bases by extracting information from text sources. In ISMB-99 (1999)
Meng Helen M., Wai-Kit Lo, Chen, B., Tang, K.: Generating Phonetic Cognates to handle Name Entities in English-Chinese Crosslanguage Spoken Document Retrieval. Proceedings of the Automatic Speech Recognition and Understanding (ASRU) Workshop, Trento, Italy (2001)
Bender, O., Josef Och F., Ney, H.: Maximum Entropy Models for Named Entity Recognition. In: Proceedings of CoNLL-2003, Edmonton, Canada, pp. 148–151 (2003)
Bunescu R., Mooney, R. J.: Relational markov networks for collective information extraction. In ICML-2004 Workshop on Statistical Relational Learning (2004)
Stalls, B.G., Knight K.: Translating names and technical terms in Arabic text. Proceedings of the COLING/ACL Workshop on Computational Approaches to Semitic Languages, Montral, Canada, 34–41. (1998)
Paola, V., Khudanpur, S.: Transliteration of Proper Names in Crosslingual Information Retrieval. Proceedings of the ACL 2003 Workshop on Multilingual and Mixedlanguag Named Entity Recognition, Sapporo, Japan, pp.57–60. (2003)
Mohanty, S., Balabantaray, R.C.: Name Entity Recognition in OMTrans. Communicated to International Journal of Translation (2007)
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© 2009 Indian Institute of Information Technology, India
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Balabantaray, R.C., Mohanty, S., Das, R.K. (2009). A Hybrid Approach for Transliteration of Name Entities. In: Tiwary, U.S., Siddiqui, T.J., Radhakrishna, M., Tiwari, M.D. (eds) Proceedings of the First International Conference on Intelligent Human Computer Interaction. Springer, New Delhi. https://doi.org/10.1007/978-81-8489-203-1_22
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DOI: https://doi.org/10.1007/978-81-8489-203-1_22
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-8489-404-2
Online ISBN: 978-81-8489-203-1
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