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International Conference on Smart Trends for Information Technology and Computer Communications

SmartCom 2016: Smart Trends in Information Technology and Computer Communications pp 285–291Cite as

An Approach for Efficient Machine Translation Using Translation Memory

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 628))

Abstract

Since 1980s, Translation Memory (TM) have been accessible. It becomes an important language technology to assist the translation. It is a database that saves “segments”, which may be sentences, paragraphs or sentence-kind elements. Tree Adjoining Grammar (TAG) is planned to use along with Machine Translation System (MTS). To make efficient machine translation and to reduce the response time of online machine translation, we come up with the use of a TM. The combined architecture of machine translation with translation memory is indicated. To make the translator’s task faster, more efficient and easier, translator tools were designed. Translation tools were designed with the objective to minimize monotonous translation work.

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References

  1. Joshi, A.K., Levy, L.S., Takahashi, M.: Tree adjunct grammars. J. Comput. Syst. Sci. 10(1), 136–163 (1975)

    Article  MathSciNet  MATH  Google Scholar 

  2. Biçici, E., Dymetman, M.: Dynamic translation memory: using statistical machine translation to improve translation memory fuzzy matches. In: Gelbukh, A. (ed.) CICLing 2008. LNCS, vol. 4919, pp. 454–465. Springer, Heidelberg (2008). doi:10.1007/978-3-540-78135-6_39

    Chapter  Google Scholar 

  3. Zhechev, V., Genabith, J.V.: Seeding statistical machine translation with TM output through tree-based structural alignment. In: SSST-4 4th Workshop on Syntax and Structure in Statistical Translation, Beijing, China, pp. 43–51, 28 August 2010

    Google Scholar 

  4. Wang, K., Zong, C., Su, K.: Integrating translation memory into phrase-based machine translation during decoding. In: The 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013), Sofia, Bulgaria, 4–9 August 2013

    Google Scholar 

  5. Simard, M., Isabelle, P.: Phrase-based machine translation in a computer assisted translation environment. In: The Twelfth Machine Translation Summit (MT Summit XII), pp. 120–127 (2009)

    Google Scholar 

  6. Fuzzy Match Algorithm. http://en.wikipedia.org/wiki/Fuzzy_string_searching

  7. Nadeau, D., Sekine, S.: A survey of named entity recognition and classification. Lingvisticae Investigationes 30(1), 3–26 (2007)

    Article  Google Scholar 

  8. Tomar, A., Bodhankar, J., Kurariya, P., Anarase, P., Jain, P., Lele, A., Darbari, H., Bhavsar, V.C.: Parallel implementation of machine translation using MPJ express. In: Proceedings of the National Conference on Parallel Computing Technologies (PARCOMPTECH), Bangalore, India, pp. 223–233. Center for Development of Advanced Computing (CDAC), 21–23 February 2013

    Google Scholar 

  9. Tomar, A., Bodhankar, J., Kurariya, P., Anarase, P., Jain, P., Lele, A., Darbari, H., Bhavsar, V.C.: High performance natural language processing services in the GARUDA grid. In: Proceedings of the National Conference on Parallel Computing Technologies (PARCOMPTECH), Bangalore, India, pp. 249–261. Center for Development of Advanced Computing (CDAC), 21–23 February 2013

    Google Scholar 

  10. Barmon, C., Faruqui, M.N., Battacharjee, G.P.: Dynamic load balancing algorithm in a distributed system. North-Holland Microprocess. Microprogram. 29(5), 273–285 (1990/1991)

    Google Scholar 

  11. Zadrozny, W.: Natural language processing: structure and complexity. In: Proceedings of the SEKE 1996, 8th International Conference on Software Engineering and Knowledge Engineering, Lake Tahoe, pp. 595–602 (1996)

    Google Scholar 

  12. Rogers, J.: A Unified Notion of Derived and Derivation Structures in TAG. University of Central Florida, Gainesville (1997)

    Google Scholar 

  13. Ramanathan, A., Hegde, J., Shah, R.M., Bhattacharyya, P., Sasikumar, M.: Simple syntactic and morphological processing can help English-Hindi statistical machine translation. In: Proceedings of the Third International Joint Conference on Natural Language Processing, vol. I, Hyderabad, India, pp. 513–520. Asian Federation of Natural Language Processing (AFNLP), January 2008

    Google Scholar 

  14. Venkatapathy, S.: Machine translation for English to Hindi. In: Proceedings of the International Conference on Natural Language Processing (2008)

    Google Scholar 

  15. Venkatapathy, S., Bangalore, S.: Discriminative machine translation using global lexical selection. ACM Trans. Asian Lang. Inf. Process. 8, 8 (2009)

    Article  Google Scholar 

  16. Ramanathan, A., Choudhary, H., Ghosh, A., Bhattacharyya, P.: Case markers and morphology: addressing the crux of the fluency problem in English-Hindi SMT. In: Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint in Proceedings on Natural Language Processing of the AFNLP, vol. 2, Suntec, Singapore, pp. 800–808, August 2009

    Google Scholar 

  17. Bojar, O., Stranák, P., Zeman, D.: Data issues in English-to-Hindi machine translation. In: Proceedings of the Seventh Conference on International Language Resources and Evaluation (LREC 2010), Valletta, Malta. European Language Resources Association (ELRA), May 2010

    Google Scholar 

  18. Bojar, O., Diatka, V., Rychlý, P., Stranák, P., Tamchyna, A., Zeman, D.: Hindi-English and Hindi-only Corpus for machine translation. In: Proceedings of the Ninth International Language Resources and Evaluation Conference (LREC 2014), Reykjavik, Iceland. ELRA, European Language Resources Association, May 2014

    Google Scholar 

  19. Mihalcea, R., Pedersen, T.: An evaluation exercise for word alignment. In: Proceedings of the HLTNAACL 2003 Workshop on Building and Using Parallel Texts: Data Driven Machine Translation and Beyond, pp. 1–10 (2003)

    Google Scholar 

  20. Zerfass, A.: Evaluating Translation Memory Systems, Freelance Translation Tools Consultant. Holzemer Str. 38, 53343 Wachtberg Germany

    Google Scholar 

  21. Yeka, J.R., Kolachina, P., Sharma, D.M.: Benchmarking of English-Hindi parallel corpora. In: The 9th Edition of the Language Resources and Evaluation Conference (LREC-2014) (2014)

    Google Scholar 

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Authors and Affiliations

  1. Information Technology, GHRCE, Nagpur, India

    Sunita Rawat & Nekita Chauhan

  2. Computer Science and Engineering, RCOEM, Nagpur, India

    M. B. Chandak

Authors
  1. Sunita Rawat
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  2. M. B. Chandak
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  3. Nekita Chauhan
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Corresponding author

Correspondence to Sunita Rawat .

Editor information

Editors and Affiliations

  1. Stanford University, Stanford, CA, USA

    Aynur Unal

  2. IT Buzz Limited, Dagenham, UK

    Malaya Nayak

  3. Microsoft Innovation Centre, Sri Aurobindo Institute of Technology, Indore, Madhya Pradesh, India

    Durgesh Kumar Mishra

  4. Namibia University of Science and Technology, Windhoek, Namibia

    Dharm Singh

  5. Sabar Institute of Technology, Sabarkantha, India

    Amit Joshi

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© 2016 Springer Nature Singapore Pte Ltd.

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Rawat, S., Chandak, M.B., Chauhan, N. (2016). An Approach for Efficient Machine Translation Using Translation Memory. In: Unal, A., Nayak, M., Mishra, D.K., Singh, D., Joshi, A. (eds) Smart Trends in Information Technology and Computer Communications. SmartCom 2016. Communications in Computer and Information Science, vol 628. Springer, Singapore. https://doi.org/10.1007/978-981-10-3433-6_34

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  • DOI: https://doi.org/10.1007/978-981-10-3433-6_34

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3432-9

  • Online ISBN: 978-981-10-3433-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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