human translation – Vertaalbureau MOTTE

Some people claim they translate tens of thousands of words per day, thanks to the use of AI.

But how strong are those claims actually?

I don’t mean those people are lying. I mean “What do they actually call a translation?”

Recently I got a telling example of a job I did myself: 166 000 words in two days! I’m not kidding you. It means I did over 83 000 words PER DAY.

But here’s the thing: it were only 9 500 words to be checked, of course spread over several sentences (or translation units, as we call that in the translation business). In those source sentences words originally written in caps were replaced by tags. The only thing I had to do, was replacing the words in the translation by those tags.

That means the 166 000 words had already been translated. Only some of them had to be replaced.

I needed 2 days for that job, which means I did almost 5000 words per day. The tricky part was the tags had to end up in the right position and they had to fit in the grammatical structure. Because of that, the translation sometimes had to be rephrased.

It shows that claims of tens of thousands of words translated per day don’t tell us anything if we don’t get a detailed analyses of the work. How much if the original words have to be translated? How much can be skipped entirely? How many translation units only demand a partial translation or retranslation?

We have to be careful to take bold claims about huge translation outputs at face value, because anyhow, a human translator is not able to do much more than 2500 or 3000 words per day from scratch, with or without AI, or MT as we call it in the translation business.

Translation refers to the process of converting written or spoken words in one language into another language. For the case of simplicity, we will treat ttem both as the same.

Translation can be done through various methods such as machine translation, human translation, or a combination of both.

Translation can also refer to converting non-linguistic forms of information, such as mathematical equations or musical notation, into other forms. But that doesn’t concern us here.

There are several forms of machine translation, including:

Rule-based machine translation (RBMT): This method uses a set of pre-defined grammar rules and dictionaries to translate text from one language to another.
Statistical machine translation (SMT): This method uses statistical models that are trained on large amounts of parallel text data to translate text.
Neural machine translation (NMT): This method uses neural networks to translate text. NMT models have been shown to produce translations that are often more accurate and natural-sounding than those produced by other forms of machine translation.
Hybrid machine translation: This method combines the strengths of different machine translation methods, such as RBMT and SMT, to produce more accurate translations.
Interactive machine translation (IMT) : this form of machine translation allows the user to interact with the machine during the translation process, correcting and providing feedback on the translations produced.
Post-editing machine translation (PEMT) : this form of machine translation allows a human translator to check and correct machine-generated translations.

There are several forms of human translation, including:

Professional translation: This form of translation is done by trained and experienced translators, who are often certified by professional organizations. Professional translations are usually done for official documents, legal contracts, and other important texts.
Community translation: This form of translation is done by volunteers or members of a community who translate text for the benefit of their community. Community translation is often used for non-profit or social impact projects.
Literary translation: This form of translation is done for literary works, such as novels, poems, and plays, to make them accessible to readers in other languages. Literary translators are often writers themselves, and pay particular attention to preserving the style and tone of the original text.
Simultaneous translation: This form of translation is done while the speaker is still speaking, which is often used in conferences, meetings and other events where multiple languages are spoken.
Consecutive translation: This form of translation is done after the speaker has finished speaking, which is often used in interviews, meetings and other events where multiple languages are spoken.
Audiovisual translation: This form of translation is done for audiovisual materials such as movies, TV shows, and video games, it includes subtitling, dubbing, and voice-over.

There are several combinations of machine translation and human translation, including:

Machine-assisted translation: This form of translation uses machine translation as a tool to help a human translator produce a more accurate and efficient translation. The translator can use the machine-generated translation as a starting point and then make any necessary corrections and improvements.
Post-editing machine translation (PEMT): This form of translation uses machine translation to generate a first draft of the translation, which is then reviewed and corrected by a human translator. This is often used for large-scale projects where speed and cost-effectiveness are important.
Hybrid machine translation: This form of translation combines the strengths of different machine translation methods, such as rule-based and statistical machine translation, to produce more accurate translations. The output of the machine translation is often reviewed and corrected by a human translator.
Interactive machine translation: This form of translation allows the user to interact with the machine during the translation process, providing feedback and corrections on the translations produced. The user can also provide additional information and context to the machine to improve the translation.
Human-in-the-loop machine translation: This form of translation uses machine translation as a tool to help a human translator, who can provide feedback and corrections to the machine, which will then adjust its output accordingly. This can improve the final translation and the efficiency of the process.