Machine Translation Using Neural Networks

Student: Markhaev Atabek

Educational Programme: Business Informatics (Bachelor)

Year of Graduation: 2020

The purpose of this paper is to study and implement in practice a model of machine translation based on neural networks. Recently, machine translation models based on neural networks have started to outpace statistical models both in terms of translation quality and in terms of transition of the sentence context from the source language. The process of building the model will be described and the results will be evaluated using the BLEU (bilingual evaluation understudy) metric, which is the most common in machine translation studies.

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