AI & Language Translation: How to Train Your Machine Translation Engine? – Analytics Insight


Welcome to the world of AI and Language translation

The delayed translation process might be a major impediment to your global aspirations. It holds you back, putting unneeded impediments in your path to worldwide expansion.

As a result, an increasing number of businesses are turning to machine translation ways to reduce translation turnaround time and get more information to market faster. In regards to the level of quality it can create, machine translation has also gone a long way.

If you’re a part of the training procedure, you might be wondering how these engines keep producing higher-quality translations over time.

What are AI translators?

AI translators are digital technologies that employ powerful artificial intelligence to translate not just the letters that are typed and spoken, but also the content (and occasionally the mood) of the message. This yields higher accuracy and fewer misconceptions than basic machine translation.

Rather than asking your professor what a word or phrase says, you can now quickly discover an app that instantly translates a different language to your native tongue.

Language recognition software is used by virtual assistants such as Siri, as well as language study programmes such as Duolingo and Rosetta Stone. To detect the spoken language, this programme employs speech recognition algorithms. It then analyses the sound to generate text.

How are AI translators advancing?

Digital translators are improving all the time. AI has evolved significantly as a result of the development of neural machine translation, or NMT. Because of its capacity to manage enormous volumes of data, this technology works extremely effectively, allowing firms like Google to provide higher-quality results. There is good news! This means you’ll have fewer embarrassing mistranslation incidents.

How can AI translators help you?

When it comes to language learning, AI has enormous promise. One significant advantage is that it speeds up everything. Allowing your phone or tablet to perform specific chores in the class can help to broaden learning while providing you more time to concentrate on other things. Previously, you had to painstakingly search a dictionary for a term. You may now just utilise an app to handle all of the hard work for you.

AI translators may also make travelling a lot simpler, especially if you’re going somewhere like Beijing, where not just the language, as well as the alphabet, is foreign! When interacting with locals or buying food in a restaurant, these applications and services might come in handy. Simply holding your phone over a menu will allow you to interpret the meals and converse with the waitress using your microphone.

How to Train Your Machine Translation Engine?

Requirements of machine translation engines training

To begin, a foundation engine is essential to a bespoke engine. Translation suppliers with a lot of experience have access to foundation engines that can help you design the machine you want to utilise for your translation.

These foundation engines are dedicated to a single language pair and vertical, such as English-to-Japanese or German-to-English engineering marketing, for example.

By combining these foundation engines with previously translated material from your firm, a machine may be better taught to translate your material, learning your brand terminology, stylistic preferences, and more.

It helps to have a huge number of high-quality, already translated information to be the most effective at the start line.

Other multilingual resources that might be very useful are:

  • Do-not-translate lists
  • Style guides
  • Glossaries

Don’t worry if you don’t have these resources or a large amount of translated information to work with. You can still train a machine translation algorithm; just keep in mind that learning your company’s business voice will take a bit longer.

Usually, the training process takes 4 to 6 weeks, during which we run your material through the engine and evaluate (and re-test) the first result.

Engines can continue to improve with regular maintenance

However, the training process does not end there. Your translation company will keep an eye on your engines throughout time in order to increase the output quality even further. After all, everyone, including robots, makes errors.

Working with a machine, on the other hand, has the advantage of being constant in its errors. As a result, after they’ve been repaired, your translation provider will be able to resolve the error indefinitely (so that pesky word choice won’t appear in your translation output).

What steps are taken to remedy these errors? The linguist’s revisions are automatically updated into your translation memory if you have a post-edit phase after machine translation. As a result, the proper version of that section will appear in your translated text anytime your translation memory is used.

Consider machine translation engine training to be a method. In other words, clients who are satisfied with machine translation perceive early results to be indications rather than ultimate instances of quality. Over time, the more work you put through your machine, the better it gets at delivering correct translations to you.

A general guideline

Without any modification, certain raw machine translation results may be of adequate standard. This is entirely dependent on your specific requirements, quality specification, and engine-level of maturity.

However, it may not be enough for public-facing material.


AI translation tools are fantastic for self-study and classroom usage, but the translations they create often need to be double-checked by a human since they make glaring mistakes.

They also lose the human aspect; yet, if travelling overseas, they may be quite beneficial in emergency situations, such as looking up a term or ordering something from the pharmacist. However, it is difficult to develop connections and thrive only via the use of digital translators such as text or voice translators.