Although a small number of English to Hindi WT systems are already available, the outputs produced by them are not of high quality all the time. Through this work we intend to analyze the difficulties that lead to this below par performance, and try to provide some solutions for them. There are several other major languages (e.g., Bengali, Punjabi, Gujrathi) in the Indian subcontinent. Demand for developing WT systems from English to these languages is increasing rapidly. But at the same time, development of computational resources in these languages is still at its infancy. Since many of these languages are similar to Hindi, syntactically as well as lexicon wise, the research carried out here should help developing WT systems from English to these languages as well. The major contributions of this research may be described as follows: 1) Development of a systematic adaptation scheme. We proposed an adaptation scheme consisting of ten basic operations. These operations work not only at word level, but at suffix level as well. This makes adaptation less expensive in many situations. 2) Study of Divergence. We observe that occurrence of divergence causes major difficulty for any WT systems. In this work we make an in depth study of the different types of divergence, and categorize them. orologi replica

This paper was withdrawn due to certain technical errors.

References

1. Ansell, M.: 2000, English Grammar: Explanations and Exercises, Second edn, http://www.fortunecity.com/bally/durrus/153/gramdex.html.
2. Arnold, D. and Sadler, L.: 1990, Theoretical basis of MiMo, Machine Translation 5(3), 195{222
3. Bender, E.: 1961, HINDI Grammar and Reader, University of Pennsylvania Press, University of Pennsylvania South Asia Regional Studies, Philadelphia, Pennsylvania.
4. Bennett, W. S.: 1990, How much semantics is necessary for MT systems?, Proceedings of the Third International Conference on Theoretical and Methodological Issues in Machine Translation of Natural Languages, Vol. TX, Linguistics Research Center, The University of Texas, Austin, pp. 261.
5. Bharati, A., Sriram, V., Krishna, A. V., Sangal, R. and Bendre, S.: 2002, An algorithm for aligning sentences in bilingual corpora using lexical information, International Conference on Natural Language Processing, Mumbai.

Back