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How AI Is Changing the Game in the Field of Auto-translation

Artificial intelligence has come a long way and in this post we’re going to take a look at how AI is changing the shape of auto-translation.

Auto-translation

Image Source: Google Translate

One of the biggest challenges with auto-translation is the fact that it’s so hard to get the context right. Take synonyms, for instance. A plant can be a green multicellular organism, or it can be a colloquial expression for a factory.

The difference is determined by a context, but, in the past, it was impossible for a machine or an algorithm to accurately establish this context. But is AI development getting smart enough to understand intent in the field of auto-translation and this post is going to take a look at how.

Sure, there are some fields in which AI won’t be able to replace human translators regardless of the development (like with translating poetry). Still, even if auto-translation isn’t perfect, it does have its numerous benefits.

With all of this in mind, let’s dig a bit deeper into how AI is changing the game in the field of auto-translation.

Benefits of Auto-translation

Although auto-translation still has its flaws, there are numerous advantages, as well. The potential benefits of auto-translation are mostly in terms of pragmatism and time/resource efficiency.

Machine translator is not paid by the word or by the number of pages. This means that you pay the license or subscription for the tool and use it as much as you need. Professional translators (especially seasoned ones) can be quite expensive. The idea that any bilingual person can be a translator is one of the biggest translation myths out there. What you need is a translation veteran, and they do not work for pebbles.

Another benefit of auto-translation is the fact that it is instant. Waiting for a translation, especially a quality translation, can take forever. If the accuracy is not paramount and the reader wants to understand the basic context, there’s no downside to using it, either. As long as you’re aware that the translation is not 100% accurate and take it with a grain of salt, using it is quite safe.

Availability is one of the biggest advantages here. As long as you have your device on you (which is all the time), you have the tool for translation available. No human translator is available 24/7.

Introducing Auto-translation

The accuracy of auto-translation is rapidly growing. Through tech concepts like semantic AI, the algorithm is developing a much more organic understanding of the language. In a way, it sees the language as we do, for the very first time. So, you can start using these tools early on, and rest assured that they’ll become more and more sophisticated in the next couple of years.

Remember that with every new technology or tech trend, it might take a while to implement it into your organization. This is why introducing auto-translation early on gives you a head start and allows your team to get accustomed to it.

One more thing worth understanding is that auto-translation may be of immense assistance to your own translators. As we’ve mentioned, the biggest problem with auto-translation starts when you trust its accuracy 100%. Even human translators can make mistakes.

Instead of relying on one or the other, the ideal solution would be to use them both to your advantage.

Future of Language Learning

The biggest problem with learning a language through translation is the fact that it lacks context. For instance, while learning a language, you could travel to the target location where the language in question is a mother tongue and talk to locals.

The biggest disadvantage of this plan is the fact that they might use words that you don’t know. Moreover, during the lower levels of language proficiency, they might not even be able to explain them descriptively.

This is one of the reasons why having a tool that can translate individual words can make so much of a difference. You see, traditional text translation is one thing, but in live conversation, you also have the information presented in the form of non-verbal communication. Being a participant in the conversation may, therefore, provide you with an opportunity to understand the context of the translated word much more accurately.

All of this combined makes it more than evident why auto-translation is a milestone in language learning.

One more application worth mentioning here is that there’s room in the field of formal education for auto-translation. AI designed for translation could provide a more unbiased estimate of one’s language-learning performance. This type of testing would be more accurate, quicker, and applicable in even some of the harder tests.

Digital Marketing Applications

When it comes to digital marketing, specifically SEO, it’s usually hard to go for multilingualism. It simply seems like it doesn’t pay off, seeing as how all the content you create becomes available to a minimal audience. With the help of auto-translation, this concept changes entirely.

Translating content into multiple languages will drastically expand your target audience. Keep in mind that while auto-translation works in all possible directions, X language to English, is probably a default. This means that it is a pairing of the X language that is worked on the most, which provides it with the highest accuracy and reliability.

Ideally, if you have an audience that belongs to several language groups, it’s better to rely on traditional content translation. There’s nothing wrong with having a blog in 3-4 languages. However, this is a costly affair that requires a lot of work. Also, you might want to go beyond these several languages and provide worldwide support. In that scenario, auto-translation and machine translation are the right calls.

Problems

One of the biggest challenges of auto-translation is the so-called untranslatable words. You see, every language is a perfect fit for the culture of its speakers. This is why Inuit have 16 different words for snow (different kinds of snow), while Italians have dozens of expressions for coffee.

In order to make a perfect translation, both of these languages would need to have words that are perfect (or almost perfect) equivalents. However, a human translator can be resourceful and use descriptive phrases or find a translation that keeps the same meaning.

In the introduction, we’ve mentioned the translation of poetry as one of the major problems. A poem is a piece of art, and it evokes different types of feelings in its readers. These feelings are expressed through the tonality, mood, spirit, and context of the poem. Needless to say, seeing as how the algorithm can’t “feel” this in a poem, they can’t translate it either. Translating a poem is not a common translation. It’s like rewriting it in a different language. An algorithm can hardly emulate such a creative task.

In Conclusion

While it is true that auto-translation has advanced quite drastically, it is also true that translation is a creative process. As such, it depends on more than just knowledge or skill. Two translators who have the same formal education will give different qualities of translation. The difference is in the talent of the translator (like with any other creative process). Still, the AI helps understand the context a lot better, which already makes a world of difference.

Nonetheless, it’s highly unlikely that human translators will become obsolete anytime soon (if ever). If anything, the AI advancement in the field of auto-translation might provide them with more sophisticated tools of work, thus allowing them to become even more efficient and accurate.

 

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