How Translation Localization Software Works & How It's Used

What is translation localization?

Translation localization is the process of adapting a piece of content in full, for a different audience. If we break the phrase down, "translation" is converting written words, verbatim, from one language to another. "Localization" refers to the complete process of adapting a piece of content in full, for a foreign audience, going beyond simply finding equivalent words in another language.

Where translating work is concerned with word choice & meaning, localization is concerned with linguistic & cultural expression. It adapts the content for a new culture, language, syntax & intent. If you have ever watched a foreign film with subtitles on, you can literally experience the difference between the two concepts. The actors are saying a lot on screen, but the translation in English doesn't quite make sense. Leaving you with an impression that a lot was quite literally, lost in translation. Because the focus was purely on language translation, rather than capturing the nuance and idiosyncrasies from the source language through localization, and into the English language.

How does translation localization software work?

Translating from one language to another was one of the initial uses for computers. Despite all the achievements and advancements in computing and machine learning along the way, it wasn't until the early 2000s that the true power of computers, data and hardware really took the world by storm. Which was fueled, in large part, by Google and other fellow tech giants like IBM for example.

These tech pioneers put forth a great deal of effort and spent exorbitant amount of time on machine learning & training. Which eventually became the basis of all translation localization software. Today, there are 3 common types of machine translation and localization including:

- RBMT or Rule Based Machine Translation: the earliest & simplest form that relies upon a large set of rules to complete translation. Similar to mathematic equations, these machines are outdated & rigid as they produce low quality translations.
- SMT or Statistical Machine Translation: By applying a statistical model of phrases, sentences and the relationship between words, these machines are able to "successfully complete" a translation by meeting a certain percentage of the source text. Success with this type is subjective, and shares many of the same issues as RBMT.
- NMT or Neural Machine Translation: by mimicking the neural pathways in the human brain, these machines are able to "learn" new languages and improve their knowledge. Rather than following predefined rules, or by only meeting a certain percent for translation, this type is able to decode source text and anticipate future translations.

How is translation localization software used?

A translator is a professional, who is fluent in both the text's original language (the source) and the other language (the target). They frequently use translator machines and software to get their work done. In order to do their jobs correctly, they must undergo specific translator localization training first. You might be wondering "why should I take a translator certificate course when there is A.I?" And the simple answer to that is: A.I is a tool. It is equipment.

In professional settings like hospitals and even courts of law, translators use translation localization to remember past sessions. The machines store records, and can help translators immensely. Remote interpreting services like VRI (Video Remote Interpreting) and OPI (Over the Phone Interpreting) rely upon the same machines. But no matter how often these machines are used, we still need professional translators to oversee the process. Especially where legal and medical records are concerned.

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