Machine Translation
approaches and limitations
DOI:
https://doi.org/10.14393/DL32-v11n5a2017-21Keywords:
Machine Translation, Computational Linguistics, Rule-based machine translation, Statistical machine translation, Neural machine translationAbstract
Machine Translation is one of the main fields and applications of Computational Linguistics (CL). In a machine translation system, the information in a source language, provided as input to the system, is transformed into an equivalent version in the target language. Despite more than 70 years of researches regarding machine translation field, the main approaches proposed have limitations. In this paper, we discuss three of these approaches: rule-based machine translation, statistical machine translation, and neural machine translation. In this article, we present a brief description of each approach, accompanied by examples that help to understand the limitations mentioned.Downloads
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