https://orcid.org/0000-0003-0341-2927
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ABSTRACT
Machine translation has become the most challenging as well as demanding field of research and as a result, to develop a fully automatic 100% correct machine translation system has not been achieved till date. More than 7000 of languages are being used worldwide for communication purposes and in India alone 22 languages have been recognized as official languages for communication purposes. Various efforts have been made to solve this problem by different researchers using different approaches. With the enhancement in technology and internet, automatic translation has become more important to share the knowledge. The authors in this paper described a mechanism of translation using machines for one of the ancient Indian Language Sanskrit to the latest computer understandable language Universal Networking Language (UNL). The proposed system uses two databases: one for the analysis purpose consists of more than 300 rules and the other for the generation of UNL which consists of about 1500 rules. For the performance evaluation, the authors selected 500 Sanskrit sentences in such a way that covers maximum UNL relations from various sources. The sentences are manually converted from English to Sanskrit language taken from Spanish Language center, Hindi to English language taken from IIT Bombay Hindi–UNL expressions and NCERT class 8th Sanskrit book titled “Ruchita Part 3”. The proposed system achieves a BLEU score of 0.85. The proposed system gives 93.18% efficiency in resolving UNL relation successfully.
ACKNOWLEDGEMENTS
The authors would like to thank to Prof. Amba Kulkarni and her students for allowing the use of Sanskrit parser developed by them which helps in the verification of the correct POS and Morphological analysis of the Sanskrit Sentences. The authors also like to thank Achaarya Sunita Dhankhar, Achaarya Hemendra Kumar and Shastri Sanjay Sharma for their help in translating sentences into the Sanskrit language The authors also take the opportunity to thank Prof. Jindagi Kumari (Professor of English) for proof-reading and improving the language.
Additional information
Notes on contributors
Sitender
Sitender completed his BE (Information Technology) and MTech (Computer Engineering) from MDU Rohtak in 2004 and 2008. Currently, he is pursuing PhD from Thapar University Patiala. His area of research is machine translation for Indian Languages. He is working as an Assistant Professor in the Department of IT at Maharaja Surajmal Institute of Technology (MSIT), Janakpuri, Delhi. He is a professional member of IEEE and Branch Counselor of IEEE MSIT Student Branch, New Delhi.
Seema Bawa
Seema Bawa holds MTech (Computer Science) degree from IIT Khargpur and PhD from Thapar Institute of Engineering & Technology, Patiala. She is currently a Professor in the Computer Science and Engineering Department at Thapar University, Patiala, since September 2010. Her areas of research interests include parallel, distributed grid and cloud computing, VLSI testing, energy aware computing and cultural computing. She has been Coordinator of two national level research & development projects sponsored by Ministry of Information and Communication Technology. She is the author/co-author 111 research publications in technical journals and conferences of international repute. She has supervised eight PhD and 44 ME theses so far. E-mail: [email protected]