Hybridization Based Machine Translations for Low-Resource Language with Language Divergence

A hybridised form of direct and rule-based language processing is used in this paper to present a Machine translation system from Sanskrit Hindi. The divergence between Hindi also discussed paper, along with proposition for how handle it. Sanskrit-Hindi bilingual dictionaries, Grammatical corpus analyses rule base, have all been the projected system. system's ability access data various vocabularies bases utilised expansion has improved by usage Elasticsearch technique. Additionally, novel technique that builds parse tree parsing table presented paper. processes input sentence using approach Context Free Grammar normal processing. No standard corpora available Translation which designed developed proposed work. specific produced dictionaries. achieved Bilingual Evaluation Understudy (BLEU) score 51.6 percent after being tested Python's natural toolkit API. performs better than current systems when compared cutting-edge systems, according comparison.