Enhancing Bi-Lingual Example Based Machine Translation Approach

Manish Rana, Mohammad Atique

Fuzzy Logic, Machine Translation, Machine Learning, NLP, etc.

This research paper shows the implementation of the work carried in machine translation using machine learning algorithm taking in consideration bi-lingual i.e. English to Hindi translation based on fuzzy technique. Model is implemented in Python taking input in English and translating to Hindi as output. It consists of a trainee dataset containing English equivalent Hindi sentences. Initial program run to train the application with the training set data. Minimum one million datasets are taken based on Microsoft’s vast collection of datasets .After implementation of the program and comparison with other techniques used in such research, the result found to achieve efficiency of 80% and above. The research done on the following machine translation shows a significant achievement in the relevant area. Further it opens a new gateway for improving the research on machine translation.

10.22161/ijaers/3.10.2