Corpus based Machine Translation System with Deep Neural Network for Sanskrit to Hindi Translation
Muskaan Singh, Ravinder Kumar, Inderveer Chana
Abstract
Sanskrit language is the mother of almost all Indian languages. The main requirement in Sanskrit domain is to translate the life-transforming stories (epics), Vedas etc. to make them available in other languages, for public at large. In the field of machine translation system there is need to develop a machine translation system which translate Sanskrit language to Hindi. So, the main focus of this work is to propose a new corpus-based translation system for Sanskrit to Hindi translation where Bhagvad Gita – the song of the lord is used as an input data. In this work, Deep neural network is used for training where input data is passed to neural network after data analysis and processing which then performs auto-tuning that help to make this model better. Target text is prepared using this proposed model and achieves better BLEU Score and Word Error Rate.