Abstract
This paper presents a case study of example-based machine translation system from Hindi to English. We have used OpenNMT, which is an open-source of MIT project, for this purpose. This tool is based on neural machine translation and deep learning methodologies. It is a library for learning, training, and deploying neural machine translation models. It has been observed that the BLEU score of the system is increasing with the increasing number of epochs in the training.
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Pathak, A.K., Acharya, P., Balabantaray, R.C. (2019). A Case Study of Hindi–English Example-Based Machine Translation. In: Chattopadhyay, J., Singh, R., Bhattacherjee, V. (eds) Innovations in Soft Computing and Information Technology . Springer, Singapore. https://doi.org/10.1007/978-981-13-3185-5_2
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DOI: https://doi.org/10.1007/978-981-13-3185-5_2
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