Quantum neural network based machine translator for English to Hindi

This paper presents the machine translation system for English to Hindi which is based on the concept of machine learning of semantically correct corpus. The machine learning process is based on quantum neural network (QNN), which is a novel approach to recognize and learn the corpus pattern in a realistic way. It presents the structure of the system, machine translation system and the performance results. System performs the task of translation using its knowledge gained during learning by inputting pair of sentences from source to target language i.e. English and Hindi. Like a person, the system also acquires the necessary knowledge required for translation in implicit form by inputting pair of sentences. The effectiveness of the proposed approach has been analyzed by using 4600 sentences of news items from various newspapers and from Brown Cuprous. During simulations and evaluation, BLEU score achieved 0.9814 accuracy, NIST score achieved 7.3521, ROUGE-L score achieved 0.9887, METEOR score achieved 0.7254 and human based evaluation achieved 98.261%. The proposed system achieved significantly higher accuracy than AnglaMT, Anuvadaksh, Bing and Google Translation.