SANSUNL: A Sanskrit to UNL Enconverter System. Issue 1 (2nd January 2021)

• Record Type: Journal Article
• Authors: Sitender, ; Bawa, Seema
• Is Part Of: IETE journal of research. Volume 67:Issue 1(2021)
• Page Start: 117
• Page End: 128
• Publication Date: 2021-01-02
• Subjects: Artificial intelligence -- Deconverter -- Enconverter -- Morphology -- Natural language -- Natural language processing -- Semantics -- Syntactic; Electronics -- Periodicals; Telecommunication -- Periodicals; Electronics; Telecommunication; Periodicals; 621.38
• DOI: 10.1080/03772063.2018.1528187
• Languages: English
• ISSNs: 0377-2063

Abstract

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.