Machine translation is a method of translation that uses artificial intelligence designed to translate text from one language to another without human editor involvement.
The process of machine translation involves taking source text in one language and translating it into a target language using a set of predetermined rules. Machine translation has made great progress in accuracy as well as fluency in recent years, thanks to improvements in neural network technology. Nowadays, there are various uses of machine translation such as applications, website localization, real-time conversation translations, and document translations.
There are two main machine translation approaches: rule-based and statistical methods.
1) Rule-based methods involve developing a set of rules that map one language to another.
2) Statistical methods use large amounts of data to learn how to translate between languages.
Recent advances in machine translation have been driven by the increasing availability of data and computational power and by advances in neural network technology. These advances have made it possible for machine translation systems to produce translations that are often indistinguishable from those produced by human translators.
Despite these advances, machine translation cannot be considered as a trustable source for accurate translation results. For example, translating idiomatic expressions and understanding context can be difficult for machines. The current state of machine translation systems is that there seems to be a long way to go before replacing human translators or perhaps not completely possible at all.
Can Machine Translation Replace Human Translation?
Machine translation can be useful comparison to human translation in the cases of high volumes and of course, if makes sense. For instance, many service-related companies use machine translation to help customers through an instant chat feature or quickly respond to emails. However, the translation may be inaccurate if you translate more in-depth content, such as web pages, articles, specific conversations. Therefore, a human translator should edit the content before using it.
For example, if you’re considering using tools like Google Translate to create different language versions of your website, it’s worth knowing that Google doesn’t recommend it.
Google Translate for Autogenerating Content
When translating a page, Google Translate communicates its meaning well, but it is not perfect and reads awkwardly. In addition, Google Translate might not be a helpful tool for content creation because of quality issues.
Conclusion
In summary, while machine translation may be very helpful for a translation requirement on a massive scale, it is not yet capable of doing as good job as a human translator. Therefore, we recommend checking with a human editor after using a machine translation.
