A Novel Framework for Sanskrit-Gujarati Symbolic Machine Translation System

Abstract

Sanskrit falls under the Indo-European language family category. Gujarati, which has descended from the Sanskrit language, is a widely spoken language particularly in the Indian state of Gujarat. The proposed and realized Machine Translation framework uses a grammatical transfer approach to translate the written Sanskrit language to Gujarati. Because both languages are morphologically rich, studying the morphology of each item is difficult but necessary to incorporate into implementation. To improve the implementation accuracy and translation clarity, an in-depth research of the creation of Nouns, Verbs, Pronouns, and Indeclinables, as well as their mappings, has been carried out. Tokenization, lemmatization, morphological analysis, Sanskrit-Gujarati bilingual synonym-based dictionary, language synthesis, and transliteration are the proposed framework's primary components. The implementation outcome was tested on 1,000 phrases, using the automated Bilingual Evaluation Understudy (BLEU) scale which yielded a value of 58.04 It was also tested on the ALPAC scale, yielding the Intelligibility score of 69.16 and the Fidelity score of 68.11. The results are encouraging and prove that the proposed system is promising and robust for the implementation in the real world applications.