Interlingua-based English–Hindi Machine Translation and Language Divergence
Machine Translation
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Precision and recall of machine translation
NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
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The development of Machine Translation (MT) system for ancient language like Sanskrit is a fascinating and challenging task. In this paper, the authors handle the infinitive type of English sentences in the English to Sanskrit machine translation (EST) system. The EST system is an integrated model of a rule-based approach of machine translation with Artificial Neural Network (ANN) model that translates an English sentence (source sentence) into the equivalent Sanskrit sentence (target sentence). The authors use feed forward ANN for the selection of Sanskrit words, such as nouns, verbs, objects, and adjectives, from English to Sanskrit User Data Vector (UDV). Due to morphological richness of Sanskrit, this system uses only morphological markings to identify Subject, Object, Verb, Preposition, Adjective, Adverb, Conjunctive and as well as an infinitive types of sentence. The performance evaluations of our EST system with different methods of MT evaluations are shown using a table.