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Machine translation systems have experienced rapid progress in recent years and have become sophisticated technologies that allow excellent results, even more so with the rise of artificial intelligence. Still, human review is necessary to ensure the highest possible quality of translation.  In this blog, we will delve into this topic to discover the advantages and disadvantages of both types of translation (machine and human), and how they complement each other.

Machine Translation vs. Human Translation

A processor or computer opens a document and automatically starts translating it non-stop. In addition, in a highly efficient way, based on what it has been learning and analyzing 24/7. Machine translation (MT) translates words with high precision and extreme speed, something that cannot be achieved with human translation (HT). A competent translator can translate around 2,500 to 3,000 words per day.

But a human knows the expressions, ways of speaking and build complete sentences, contributing with his personal approach in each paragraph. In addition, he is familiar with the semantics and terminology of the language and with the cultural context of the translation target market. As expert translation engine builders, we know that machine translation processors can quickly specialize with data organized in a parallel manner. What is essential is the context, which is still within human capabilities.

In order for a translation to be as good or even (in some cases) better than the original version, it is very important to understand the context. In this situation, human translation plays an important role . We can say that the role of the translator is nowadays changing to become a “quality reviewer” of large volumes of machine translation.

When is a human translator needed?

As technology advances, neural machine translation systems process language better. Based on sophisticated tools such as ML Machine Learning and DL Deep Learning, machine processors gain the ability to continuously learn from a myriad of data embedded in the cloud. And as they learn, the translation gets better.

It is true that it is the expert hands of programmers and artificial intelligence experts who manage, select, and prioritize data and how algorithms look at certain areas of a phrase, a particular vocabulary, or consider certain lengths of phrases or sentences. However, the work of the human translator, as a linguist expert who provides situational knowledge that solves polysemies and contexts, is still very necessary when we want to guarantee the final quality of the translation in cases where:

• We want to avoid mistakes of any kind.
• We understand that context influences translation.
• It is a translation in a specialized field.
• The text will be published, and the quality and specificity of the translation are very important.

According to experts, the last two points depend on the amount of data available from the specialized field from which the translation engine has been fed. So, if we had a significant amount of parallel data from medicine, agriculture, or the legal sector, our translation engine will specialize in them by looking for relevant examples in those topics.

A competent professional translator avoids translation errors, such as false friends, or errors given by the polysemy of a term, and can correct any errors that could be in the source text (with the permission of the client/author). In addition, it adapts the text to the style required by the context and the theme.

With globalization, it is imperative that documents, marketing materials, reports, forms, websites, clinical protocols, pharmaceutical dossiers, technical manuals, etc., are translated with the appropriate contextualization and localization to the needs of each customer.   If one wants to be competitive and have global reach.