Open Access Open Access  Restricted Access Subscription Access

Challenges in Building Dogri-Hindi Statistical MT System


Affiliations
1 JJT University, Jhunjhunu, India
2 J&K Higher Education Dept, Jammu, India
3 Multani Mal Modi College, Patiala, India
 

In present time to overcome the problem of language barrier in communication, lots of researches have been done in the field of language translation. The system which is developed for translation of languages by the researchers is known as machine translation system. There are different types of Machine Translation systems are developed with the change of time and for the need of more accuracy in the translation. No doubt the development of MT systems proved to be great achievement in the field of science and technology. But such achievement was not that easy. Different challenges and issues were faced by various researchers during the development of their MT systems. This paper focuses on the challenges and problems faced during the development of Dogri-Hindi SMT system. This paper also discusses the steps that are taken under consideration to overcome that challenges.

Keywords

Statistical Machine Translation, Parallel Corpus, Translation.
User
Notifications
Font Size

  • Preeti Dubey, Shashi Pathania, Devanand, Comparative Study of Hindi and Dogri Languages with regard to Machine Translation, Language In India, Volume 11:10 October 2011,ISSN 1930-2940
  • G S Josan and G S Lehal,(2008), A Punjabi to Hindi Machine Translation System. COLING: Companion volume: Posters and Demonstrations, Manchester, UK, pp. 157-160
  • Vishal Goyal, Gurpreet Singh Lehal, (2008), Comparative Study of Hindi and Punjabi Language Scripts, Napalese Linguistics, Journal of the Linguistics Society of Nepal, Volume 23, pp 67-82
  • Philipp Koehn, Franz Josef Och, and Daniel Marcu. (2003), Statistical phrased-based machine translation, In HLT/NACL, pages 127–133
  • Franz Josef Och and Hermann Ney. (2003), A systematic comparison of various statistical alignment models , Computational Linguistics, 29(1):19–51
  • Franz Josef Och and Hermann Ney. (2002), Discriminative training and maximum entropy models for statistical machine translation , In ACL, pages 295–302
  • Paul Baker, Andrew Hardie, Tony McEnery, Richard Xiao, Kalina Bontcheva, Hamish Cunningham, Robert Gaizauskas, Oana Hamza, Diana Maynard, Valentin Tablan (2004), Corpus Linguistics and South Asian Languages: Corpus Creation and Tool Development, Lit Linguist Computing 19 (4): 509-524, DOI:https://doi.org/10.1093/llc/19.4.509, Published:01 November 2004
  • Sunita Arora, Rajni Tyagi, Somi Ram Singla, Creation of Parallel Corpus from comparable Corpus, Proceedings of ASCNT – 2010, CDAC, Noida, India, pp. 77 – 83.
  • Pardeep Kumar, Vishal Goyal, (2010), Development of Hindi-Punjabi Parallel Corpus Using Existing Hindi-Punjabi Machine Translation System and Using Sentence Alignments, International Journal of Computer Applications (0975 – 8887), Volume 5– No.9, pp.15-19
  • Alexandra Antonova, Alexey Misyurev, Building a Web-based parallel corpus and filtering out machinetranslated text, Proceedings of the 4th Workshop on Building and Using Comparable Corpora, pages 136–144, 49th Annual Meeting of the Association for Computational Linguistics, Portland, Oregon, 24 June 2011, Association for Computational Linguistics
  • Ali, Aasim, Shahid Siddiq and M. Kamran Malik, (2010), Development of parallel corpus and English to urdu statistical machine translation, International Journal of Engineering and Technology/IJENS, 1: 30-33, ISSN 2077-1185.
  • Masood Ghayoomi, Stefan Muller, PerGram: A TRALE Implementation of an HPSG Fragment of Persian, Proceedings of the International Multiconference on Computer Science and Information Technology, pp. 461–467, ISBN 978-83-60810-22-4, ISSN 1896-7094.

Abstract Views: 254

PDF Views: 3




  • Challenges in Building Dogri-Hindi Statistical MT System

Abstract Views: 254  |  PDF Views: 3

Authors

Manu Raj Moudgil
JJT University, Jhunjhunu, India
Preeti Dubey
J&K Higher Education Dept, Jammu, India
Ajit Kumar
Multani Mal Modi College, Patiala, India

Abstract


In present time to overcome the problem of language barrier in communication, lots of researches have been done in the field of language translation. The system which is developed for translation of languages by the researchers is known as machine translation system. There are different types of Machine Translation systems are developed with the change of time and for the need of more accuracy in the translation. No doubt the development of MT systems proved to be great achievement in the field of science and technology. But such achievement was not that easy. Different challenges and issues were faced by various researchers during the development of their MT systems. This paper focuses on the challenges and problems faced during the development of Dogri-Hindi SMT system. This paper also discusses the steps that are taken under consideration to overcome that challenges.

Keywords


Statistical Machine Translation, Parallel Corpus, Translation.

References