Multilingual Machine Translation in the Indian Subcontinent: Approaches,  Challenges, and Cross-Lingual Paradigms

Ved Kumar Gupta, Arvind Upadhyay, Neeraj Mehta

Multilingual Machine Translation in the Indian Subcontinent: Approaches, Challenges, and Cross-Lingual Paradigms

Authors

Ved Kumar Gupta, Arvind Upadhyay, Neeraj Mehta

Keywords:

Machine Translation, Indian Languages, Computational Paninian Grammar, Structural Isomorphism, Phrase-Based SMT, Byte-Pair Encoding.

Abstract

Machine Translation (MT) in the Indian subcontinent presents unique computational challenges due tohigh morphological complexity, flexible word order, and severe resource asymmetry among IndoAryan and Dravidian language families. This survey provides a comprehensive analysis of 51 translation architectures spanning three decades of Machine Translation

References

[1] R. M. K. Sinha, "Machine translation in India: A brief survey," Journal of Computer Science and Technology, vol. 5, no. 2, pp. 1111–1116, 2010.

[2] H. Choudhary, A. K. Pathak, and R. R. Shah, "Neural machine translation for English-Tamil," in Proc. 3rd Conf. Machine Translation (WMT), Brussels, Belgium, 2018, pp. 783–788.

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Published

2022-01-20

How to Cite

Ved Kumar Gupta, Arvind Upadhyay, Neeraj Mehta. (2022). Multilingual Machine Translation in the Indian Subcontinent: Approaches, Challenges, and Cross-Lingual Paradigms. Journal of Computational Analysis and Applications (JoCAAA), 30(1), 957–968. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/5841