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Language Translation: Enhancing Bi-Lingual Machine Translation Approach Using Python

0*, Mohammad Atique**

*-**Department of Computer Science & Engineering, SantGadge Baba Amravati University, Amravati, India.

Periodicity:June - August'2019
DOI : https://doi.org/10.26634/jcom.7.2.15597

Abstract

This paper shows the improvement in the work carried in Machine Translation as compared to the other techniques used. The work is the enhancement of “Enhancing Bi-Lingual Machine Translation Approach”. It shows the development in a Language Translation using Python, which consist of predefined packages like TextBlob and Google-API. The paper talks about enhancing Bilingual Machine Translation. English language into Indian Languages like Hindi, Marathi, Gujarati, Sindhi, Punjabi, Bengali, Urdu, and Dravidian languages. The work shown in the paper is implemented using a speech_recognition module, where speech input is taken from user so as to translate into any Indian language. After comparison with various techniques and research, the paper shows efficient result up to 94% accuracy.

Keywords

Bi-Lingual Machine Translation, Language Translation, Textblob, Speech Recognition etc.

How to Cite this Article?

Rana, M., Atique, M.(2019). Language Translation: Enhancing Bi-Lingual Machine Translation Approach Using Python, i-manager's Journal on Computer Science, 7(2), 36-42. https://doi.org/10.26634/jcom.7.2.15597

References

[1]. Aasha, V. C., & Ganesh, A. (2015, August). Machine translation from English to Malayalam using transfer approach. In 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI) (pp. 1565-1570). IEEE.

[2]. Abiola, O. B., Adetunmbi, A. O., & Oguntimilehin, A. (2015). A review of the various approaches for text to text machine translations. International Journal of Computer Applications, 120(18), 7-12.

[3]. Ahmed, S. Rahman, M. O. Pir, S. R. Mottalib, M. A., & Islam, M. S. (2003). A new approach towards the development of English to Bengali machine translation system. International Conference on Computer Information and Technology (ICCIT), 360-364.

[4]. Anju, E. S., & Kumar, K. V. M. (2014). Malayalam to English Machine Translation: An EBMT system. IOSR Journal of Engineering (IOSRJEN), 4(1), 18-23.

[5]. Ayala, B. R., & Chen, J. (2017, June). A machine learning approach to evaluating translation quality. In Proceedings of the 17^thACM/IEEE Joint Conference on Digital Libraries (pp. 281-282). IEEE Press.

[6]. Brants, T., Popat, A. C., Xu, P., Och, F. J., & Dean, J. (2007, June). Large language models in machine translation. In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL) (pp. 858-867).

[7]. Chen, J. (2016). Multilingual Access and Services for Digital Collections. ABC-CLIO.

[8]. Chen, K., Zhao, T., Yang, M., & Liu, L. (2017, February). Translation prediction with source dependency-based context representation. In Thirty-First AAAI Conference on Artificial Intelligence.

[9]. Chen, K., Zhao, T., Yang, M., Liu, L., Tamura, A., Wang, R., ... & Sumita, E. (2018). A neural approach to source dependence based context model for statistical machine translation. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 26(2), 266-280.

[10]. Corston-Oliver, S., Gamon, M., & Brockett, C. (2001, July). A machine learning approach to the automatic evaluation of machine translation. In Proceedings of the 39^th Annual Meeting on Association for Computational Linguistics (pp. 148-155). Association for Computational Linguistics.

[11]. Dasgupta, S., Wasif, A., & Azam, S. (2004). An optimal way of machine translation from English to Bengali. In ICCIT.

[12]. Dhariya, O., Malviya, S., & Tiwary, U. S. (2017, January). A hybrid approach for Hindi-English machine translation. In 2017 International Conference on Information Networking (ICOIN) (pp. 389-394). IEEE.

[13]. Ethnologue. (2016). Most Widely Spoken Languages in the World. Retrieved from http//www.infoplease.com/ ipa/A0775272.html

[14]. Haroon, R. P., & Shaharban, T. A. (2016, March). Malayalam machine translation using hybrid approach. In 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT) (pp. 1013-1017). IEEE.

[15]. Heafield, K., Pouzyrevsky, I., Clark, J. H., & Koehn, P. (2013). Scalable modified Kneser-Ney language model estimation. In Proceedings of the 51^st Annual Meeting of the Association for Computational Linguistics (Vol. 2, pp. 690-696).

[16]. Hu, X. (2016, August). Statistical Machine Translation Approach based on Dependency-to-String Model. In 2016 International Conference on Smart Grid and Electrical Automation (ICSGEA) (pp. 241-244). IEEE.

[17]. Kulkarni, A. P. (2003). Design and Architecture of 'Anusaaraka'-An Approach to Machine Translation. Satyam Techical Review, 3, 57-64.

[18]. Muntarina, K., Moazzam, G. M., & Bhuiyan, A. A. (2013). Tense based english to Bangla translation using MT system. International Journal of Engineering Science Invention, 2(10), 30-38.

[19]. Nahar, S., Huda, M. N., Nur-E-Arefin, M., & Rahman, M. M. (2017, December). Evaluation of machine translation approaches to translate English to Bengali. In 2017 20^th International Conference of Computer and Information Technology (ICCIT) (pp. 1-5). IEEE.

[20]. Nair, L. R., Peter, D., & Ravindran, R. P. (2012). Design and development of a Malayalam to English translator-a transfer based approach. International Journal of Computational Linguistics (IJCL), 3(1), 1-11.

[21]. Owczarzak, K., van Genabith, J., & Way, A. (2007). Evaluating machine translation with LFG dependencies. Machine Translation, 21(2), 95-119.

[22]. Pal, S., Pakray, P., & Naskar, S. K. (2014). Automatic building and using parallel resources for SMT from rd comparable corpora. In Proceedings of the 3 Workshop on Hybrid Approaches to Machine Translation (HyTra) (pp. 48-57).

[23]. Pareek, P. K., Swathi, K., & Shetteppanavar, P. (2017, May). An efficient machine translation model for Dravidian language. In 2017 2^nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT) (pp. 2101-2105). IEEE.

[24]. Quirk, C., & Menezes, A. (2006). Dependency treelet translation: the convergence of statistical and example- based machine-translation? Machine Translation, 20(1), 43-65.

[25]. Rahman, S. A., Mahmud, K. S., Roy, B., & Hasan, K. M. A. (2003). English to Bengali Translation using a new Natural Language Processing algorithm. In International Conference on Computer Information and Technology (ICCIT) (pp. 294-298).

[26]. Rana, M. (2015). A Review: Machine Translation Using Various Soft-Computing Tools. Multiconw-2015 Proceedings.

[27]. Rana, M., & Atique, M. (2015a). Example based machine translation using fuzzy logic from English to Hindi. In Proceedings on the International Conference on Artificial Intelligence (ICAI) (p. 354). The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp).

[28]. Rana, M., & Atique, M. (2015b). A Review: Machine Translation using Various Soft-Computing Tools: International Conference on Communication Computing & Virtualization (Vol. 2, pp. 813-816).

[29]. Rana, M., & Atique, M. (2015c). Example based Machine Translation using Various Soft Computing Techniques Review. International Journal of Scientific and Engineering Research, 6(4), 1100-1107.

[30]. Rana, M., & Atique, M. (2016a). Enhancing Bi- Lingual Example based Machine Translation Approach. International Journal of Advanced Engineering Research and Science, 3(10), 8-12.

[31]. Rana, M., & Atique, M. (2016b). Use of Fuzzy tool for example based machine translation. Procedia Computer Science, 79, 199-206.

[32]. Remya, L. B. et al. (2012). Analysis of Interlingual Translation Issues for Building Parallel Corpora. National Seminar on Relevance of Malayalam.

[33]. Ren, F., & Shi, H. (2001). Parallel machine translation: Principles and practice. In Proceedings Seventh IEEE International Conference on Engineering of Complex Computer Systems (pp. 249-259). IEEE.

[34]. Shen, L., Xu, J., & Weischedel, R. (2008, June). A new string-to-dependency machine translation algorithm with a target dependency language model. In Proceedings of ACL-08: HLT (pp. 577-585).

[35]. Sindhu, D. V., & Sagar, B. M. (2016, December). Study on machine translation approaches for Indian languages and their challenges. In 2016 International Conference on Electrical, Electronics, Communication, Computer and Optimization Techniques (ICEECCOT) (pp. 262-267). IEEE.

[36]. Sinha, R. M. K., Sivaraman, K., Agrawal, A., Jain, R., Srivastava, R., & Jain, A. (1995, October). ANGLABHARTI: A multilingual machine aided translation project on translation from English to Indian languages. In 1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21^stCentury (Vol. 2, pp. 1609-1614). IEEE.

[37]. Tiwary, U. S., & Siddiqui, T. (2008). Natural Language Processing and Information Retrieval. Oxford University Press, Inc.

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