June 10, 2019
Growing globalization of the international economy and strengthening of international communications lead to an increasing number of companies interested in successful international partnership. Thus, considerable responsibility for building a successful international market relationship falls on translation service providers.
At the same time, the translation service providers themselves rely more and more on modern technologies.
Machine translation currently stands as one of these technologies and should not be confused with the concept of automated translation.
The ultimate goal of such technology as machine translation is to achieve the best possible quality for translation output using software approach only.
On a basic level, machine translation (MT) came down to simple substitution of words in one language for words in another, but that alone in most cases did not allow to achieve even a moderate quality output. Solving this problem with neural techniques is a rapidly growing field that is leading to better translations, handling differences in linguistic typology, translation of idioms, and providing better output quality.
Improved output quality is mainly achieved by human intervention: for example, some systems are able to translate more accurately if the user customizes related software for a specific domain or unambiguously identifies which words in the text are proper names. With the assistance of these techniques, MT has proven useful as a tool to assist human translators and, in a very limited number of cases, can even produce output that can be used as is (e.g., weather reports).
Yet the potential of machine translation as a standalone technology is a subject of strong debate. The possibility of achieving fully automatic machine translation of high quality with no human intervention for most translation domains is still questioned.