SpringerLink
Log in

Machine Translation Systems for Official Languages of North-Eastern India: A Review

  • Conference paper
  • First Online:
Computational Intelligence in Communications and Business Analytics (CICBA 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1956))

  • 81 Accesses

Abstract

Language is the fundamental communication tool, and translation is a key instrument for understanding knowledge in an unknown language. Machine Translation (MT) is a Natural Language Processing tool where automated mechanisms are used to convert text from one natural language into another while retaining the sense of the text same. Though MT is a prime research field in India for many years, very limited work for the official languages of northeastern India has been done. The region is home to a diverse set of languages, many of which are classified as endangered or vulnerable. As such, there is a growing need for MT systems to facilitate communication and improve access to information in these languages. This paper shed light on the work carried out for these languages in the domain of MT and encourages researchers to advance exploration in the field. The review concludes by identifying areas for future research and development in the field of MT for the official languages of North-eastern India, including the need for more resources and tools to support the development of MT systems, as well as greater collaboration between researchers, language experts, and other stakeholders. It also provides a brief overview of how different MT methods operate.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 64.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 84.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Sanyal, S., Borgohain, R.: Machine translation systems in India (2013)

    Google Scholar 

  2. Dave, S., Parikh, J., Bhattacharyya, P.: Interlingua based English Hindi machine translation and language divergence. Mach. Transl. 16, 251–304 (2002)

    Article  Google Scholar 

  3. Okpor, M.D.: Machine translation approaches: issues and challenges. In: Proceedings of IJCSI, vol. 11, Issue 5, No. 2, September 2014

    Google Scholar 

  4. Paul, A., Purkayastha, B.S.: English to Nepali statistical machine translation system. In: Proceedings of the International Conference on Computing and Communication Systems, pp. 423–431 (2018)

    Google Scholar 

  5. Zhou, M., Huang, J.X., Huang, C.N., Wang, W.: Example based machine translation system. U.S. Patent: US 7,353,165 B2 (2008)

    Google Scholar 

  6. Sinhal, R.A., Gupta, K.O.: A pure EBMT approach for English to Hindi sentence translation system. In. J. Mod. Educ. Comput. Sci. 7, 1–8 (2014)

    Google Scholar 

  7. Wu, Y., et al.: Google’s neural machine translation system: bridging the gap between human and machine translation. ar**v abs/1609.08144 (2016)

    Google Scholar 

  8. Chatterji, S., Roy, D., Sarkar, S., Basu, A.: A hybrid approach for bengali to hindi machine translation. In: Proceedings of 7th ICON, pp. 83–91 (2009)

    Google Scholar 

  9. Barman, A.K., Sarmah, J., Sarma, S.K.: Assamese WordNet based quality enhancement of bilingual machine translation system. In: Proceedings of the Seventh Global Wordnet Conference, pp. 256–261. University of Tartu Press, January 2014

    Google Scholar 

  10. Das, P., Baruah, K.K., Hannan, A., Sarma, S.K.: Rule based machine translation for Assamese-English using Apertium. Int. J. Emerg. Technolog. Comput. Appl. Sci. 8(5), 401–406 (2014)

    Google Scholar 

  11. Baruah, K.K., Das, P., Hannan, A., Sarma, S.K.: Assamese-English bilingual machine translation. Int. J. Nat. Lang. Comput. 3(3), 73–82 (2014). https://doi.org/10.5121/ijnlc.2014.3307

  12. Singh, M.T., Borgohain, R., Gohain, S.: An English-Assamese machine translation system. Int. J. Comput. Appl.Comput. Appl. 93(4), 1–6 (2014)

    Google Scholar 

  13. Das, P., Baruah, K.K.: Assamese to English statistical machine translation integrated with a transliteration module. Int. J. Comput. Appl.Comput. Appl. 100(5), 0975–8887 (2014)

    Google Scholar 

  14. Kalita, N.J., Islam, B.: Bengali to Assamese statistical machine translation using Moses (Corpus based). In: Proceedings of the International Conference on Cognitive Computing and Information Processing (2015)

    Google Scholar 

  15. Hussain, Z., Dutta Borah, M., Hannan, A.: N-gram based machine translation for English-Assamese: two languages with high syntactical dissimilarity. Proc. Int. J. Eng. Adv. Technol. (IJEAT) 9(2) (2019). ISSN 2249-8958

    Google Scholar 

  16. Islam, S., Purkayastha, B.S.: English to Bodo phrase-based statistical machine translation. In: Proceedings of 10th International Conference on Advanced Computing and Communication Technologies, APIIT SD, pp. 207–217, Panipat. Haryana, India (2017)

    Google Scholar 

  17. Islam, S., Purkayastha, B.S.: English to Bodo statistical machine translation system using multi-domain parallel corpora. In: Proceedings of 15th International Conference on Natural Language Processing, pp. 80–86, Patiala, India (2018)

    Google Scholar 

  18. Singh, T.D., Bandyopadhyay, S.: Manipuri-English example based machine translation system. Int. J. Comput. Linguist. Appl. 1(1–2), 201–216 (2010)

    Google Scholar 

  19. Singh, T.D., Bandyopadhyay, S.: Statistical machine translation of English–Manipuri using morpho-syntactic and semantic information. In: Proceedings of the Association for Machine Translation in the Americas (2010)

    Google Scholar 

  20. Singh, T.D., Bandyopadhyay, S.: Manipuri-English bidirectional statistical machine translation systems using morphology and dependency relations. In: Proceedings of SSST-4, Fourth Workshop on Syntax and Structure in Statistical Translation, pp. 83–91, COLING, Bei**g (2010)

    Google Scholar 

  21. Singh, T.D., Bandyopadhyay, S.: Integration of reduplicated multiword expressions and named entities in a phrase based statistical machine translation system. In: Proceedings of the 5th International Joint Conference on Natural Language Processing, pp. 1304–1312, Chiang Mai, Thailand (2011)

    Google Scholar 

  22. Rapthap, B.J., Das, P.: Review: English to Khasi translation system. Int. J. Comput. Appl. (0975 – 8887) 179(9) (2018)

    Google Scholar 

  23. Thabah, N.D.J., Purkayastha, B.S.: Khasi to English neural machine translation: an implementation perspective. Int. J. Eng. Adv. Technol. (IJEAT) 9(2) (2019). ISSN 2249-8958

    Google Scholar 

  24. Pathak, A., Pakray, P., Bentham, J.: English-Mizo machine translation using neural and statistical approaches. Neural Comput. Appl.Comput. Appl. (2018). https://doi.org/10.1007/s00521-018-3601-3

    Article  Google Scholar 

  25. Shrestha, H.K.: Rule based machine translation system in the context of Nepali text to English text(2008)

    Google Scholar 

  26. Laskar, S.R., Pakray, P., Bandyopadhyay, S.: Neural machine translation: Hindi ↔ Nepali. In: Proceedings of the Fourth Conference on Machine Translation (WMT), Volume 3: Shared Task Papers (Day 2), pp. 202–207 (2019)

    Google Scholar 

  27. Khenglawt, V., Laskar, S.R., Pal, S., Pakray, P., Khan, A.K.: Language resource building and English-to-Mizo neural machine translation encountering tonal words. In: Proceedings of the WILDRE-6 Workshop @LREC2020, pp. 48–54 (2022)

    Google Scholar 

  28. Lalrempuii, C., Soni, B., Pakray, P.: An improved English-to-Mizo neural machine translation. Trans. Asian Low-Resourc. Lang. Inf. Process. 20(4), 1–21 (2021)

    Article  Google Scholar 

  29. Thihlum, Z., Khenglawt, V., Debnath, S.: Machine translation of english language to Mizo language. In: 2020 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM), pp. 92–97 (2020)

    Google Scholar 

  30. Laskar, S.R., Pakray, P., Bandyopadhyay, S.: Neural machine translation for low resource Assamese–English. In: Maji, A.K., Saha, G., Das, S., Basu, S., Tavares, J.M.R.S. (eds.) Proceedings of the International Conference on Computing and Communication Systems. LNNS, vol. 170, pp. 35–44. Springer, Singapore (2021). https://doi.org/10.1007/978-981-33-4084-8_4

    Chapter  Google Scholar 

  31. Daimary, M., Sarma, S.K., Rahman, M.: Bodo to English statistical machine translation system. Int. J. Comput. Sci. Eng. 7(5), 1731–1736 (2019)

    Google Scholar 

  32. Singh, T.D. Hujon, A.V.: Low resource and domain specific english to khasismt and nmt systems. In: 2020 International Conference on Computational Performance Evaluation (ComPE), pp. 733–737. IEEE (2020)

    Google Scholar 

  33. Thabah, N.D.J., Purkayastha, B.S.: Low resource neural machine translation from English to Khasi: a transformer based approach. In: Proceedings of the International Conference on Computing and Communication Systems: I3CS 2020, vol. 170, p. 3. NEHU, Shillong, India (2021)

    Google Scholar 

  34. Singh, S.M., Singh, T.D.: Unsupervised neural machine translation for english and Manipuri. In: Proceedings of the 3rd Workshop on Technologies for MT of Low Resource Languages, pp. 69–78 (2020)

    Google Scholar 

  35. Singh, T.J., Singh, S.R., Sarmah, P.: English-Manipuri machine translation: an empirical study of different supervised and unsupervised methods. In: 2021 International Conference on Asian Language Processing (IALP), pp. 142–147 (2021). https://doi.org/10.1109/IALP54817.2021.9675167

  36. Laitonjam, L., Singh, S.R.: Manipuri-English machine translation using comparable corpus. In: Proceedings of the 4th Workshop on Technologies for MT of Low Resource Languages (LoResMT2021), pp. 78–88 (2021)

    Google Scholar 

  37. Huidrom, R., Lepage, Y.: Introducing EM-FT for Manipuri-English neural machine translation. In: Proceedings of the WILDRE-6 Workshop @LREC2020, pp. 1–6 (2022)

    Google Scholar 

  38. Roy, A.K., Paul, A., Purkayastha, B.S.: Statistical and syllabification based model for Nepali machine transliteration. In: Mukhopadhyay, S., Sarkar, S., Dutta, P., Mandal, J.K., Roy, S. (eds.) CICBA 2022. CCIS, vol. 1579, pp. 19–27. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-10766-5_2

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, Assam University, Silchar, India

    Amit Kumar Roy & Bipul Syam Purkayastha

Authors
  1. Amit Kumar Roy
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bipul Syam Purkayastha
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Amit Kumar Roy .

Editor information

Editors and Affiliations

  1. Kalyani Government Engineering College, Kalyani, India

    Kousik Dasgupta

  2. Assam University, Silchar, India

    Somnath Mukhopadhyay

  3. University of Kalyani, Kalyani, West Bengal, India

    Jyotsna K. Mandal

  4. Visvabharati University, Santiniketan, West Bengal, India

    Paramartha Dutta

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Roy, A.K., Purkayastha, B.S. (2024). Machine Translation Systems for Official Languages of North-Eastern India: A Review. In: Dasgupta, K., Mukhopadhyay, S., Mandal, J.K., Dutta, P. (eds) Computational Intelligence in Communications and Business Analytics. CICBA 2023. Communications in Computer and Information Science, vol 1956. Springer, Cham. https://doi.org/10.1007/978-3-031-48879-5_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-48879-5_23

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-48878-8

  • Online ISBN: 978-3-031-48879-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation