Abstract
The global communication can be easily performed due to this linguist assistance. However, driving the translator to stay around is almost impossible. Thus, a technology support is needed to answer the problem. Machine translation (MT) could be the solution. It is a branch of machine learning, focused on computation of translating the source language into target language. The first type, rule-based MT (RBMT) has been evolved to various systems such as example based MT (EBMT), statistical MT (SMT), and Neural MT (NMT). Now, it is widely used as pedagogical tools, especially for who want to study the four foundational skills of foreign language learning. Its translation result is always refined, yet it is never beat the human translator.
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