Articles

 

Application of Pronominal Divergence and Anaphora Resolution in English–Hindi Machine Translation

 

Kamlesh Dutta¹, Nupur Prakash², and Saroj Kaushik³

 

¹ Computer Science & Engineering Department, National Institute of Technology, Hamirpur–177005 (HP), India (phone: +911972–3044424; fax: +91–1972–223834, e–mail: kdnith@gmail.com).

² School of Information Technology, Guru Gobind Singh Inderprastha University, Delhi. Currently she is on deputation as additional director, ICAI, India (e–mail: nupurprakash@rediffmail.com).

³ Computer Science & Engineering Department, Indian Institute of Technology. Delhi, India (e–mail: saroj@cse.iitd.ac.in).

 

Manuscript received March 23, 2008.
Manuscript accepted for publication March 04, 2009.

 

Abstract

So far the majority of Machine Translation (MT) research has focused on translation at the level of individual sentences. For sentence level translation, Machine Translation has addressed various divergence issues for large variety of languages; the issue of pronominal divergence has been presented only recently. Since the quality of translation as required by users follows coherent multi–sentence discourse structure in a specific context, the pronominal divergence helps us in understanding the nuances of translation arising out of disparity in the languages. Subsequently using clues from this divergence, the anaphora resolution system can find the correct interpretation for the given pronominal referents and other entities by resolving the inter–sentential context. In the literature, researchers have examined the issue and have proposed ways for their classification and resolution of anaphora. However for Indic languages, not many studies are available. In this paper, we discuss different aspects of pronominal divergence that affects the anaphora resolution in English Hindi Machine Translation (EHMT). The study shall be helpful in developing approaches that can explicitly use inter–sentential information in order to resolve specific types of ambiguity and which can generate coherent multi–sentence discourse structure in the target language to produce higher quality of translation Machine Translation.

Key words: Pronominal, anaphora, machine translation, divergence.

 

DESCARGAR ARTÍCULO EN FORMATO PDF

 

REFERENCES

[1] R. Mitkov, Anaphora Resolution, Pearson Education. Longman, London. 2002.         [ Links ]

[2] R. Mitkov, S. K. Choi and R. Sharp, "Anaphora Resolution in Machine Translation," in Proceedings of the Sixth International Conference on Theoretical and Methodological Issues in Machine Translation TMI95, pp. 87–95, Leuven, Belgium, 1995.         [ Links ]

[3] A. F. Gelbukh and G. Sidorov, "On Indirect Anaphora Resolution," in Proc. PACLING–99, Pacific Association for Computational Linguistics, pp. 181–190, Waterloo, Ontario, Canada, August 25–28, 1999.         [ Links ]

[4] D. Gupta and N. Chaterjee, "Identification of Divergence for English to Hindi EBMT," in Proceeding of MT Summit– IX, pp. 141–148, 2003.         [ Links ]

[5] R. Evans, "Applying Machine Learning Toward an Automatic Classification of It," Literary and Linguistic Computing, Vol. 16. No. 1, Oxford University Press, pp. 45–57, 2001.         [ Links ]

[6] http://www.cse.iitk.ac.in        [ Links ]

[7] http://202.141.152.9/matra/index.jsp        [ Links ]

[8] http://translate.google.com/        [ Links ]

[9] B.J. Dorr, "Machine Translation Divergences: A Formal Description and Proposed Solution," Computational Linguistics, Vol. 20, Number 4, pp. 597–633, 1994.         [ Links ]

[10] B. J. Dorr, L. Pearl, R. Hwa and N. Habash, "DUSTer: A Method for Unraveling Cross–Language Divergences for Statistical Word–Level Alignment," Machine Translation: From Research to Real Users, LNCS 2499, pp. 31–43, 2003.         [ Links ]