3 Common Misconceptions of Machine Translation

As technological advances enable fields like localization and translation processes to become faster and more accurate, methods that were previously perceived as complex and inaccurate (like Machine Translation) are now gaining more momentum and use across global companies.

Of course, as with the introduction of any new technology, there is bound to be questions and hesitation from experts and users in the industry. In this post, we break down some of today’s common misconceptions of MT — and the truths of each that will help you to better understand the power behind localization by way of Machine Translation.

1. There is only one type of Machine Translation.

While Machine Translation is one method out of the three main ones that companies can use to translate their content at scale, it does not mean that it is a single and static solution. In fact, contrary to popular belief, there are actually various types of Machine Translation that companies can leverage — the two main types being Rules Based Machine Translation and Statistical Machine Translation.  At a glance, Rules-Based MT is based on a specific set of rules that are developed by your experts and developers, forming a library of manually built translation lexicons can also be adjusted over time to further improve translation quality. On the other hand, Statistical MT is use computer algorithms to build a database of translations that are based on the statistical likelihood that a certain word or phrase in the source language will be another word or phrase in the target language.

What does this mean for those looking to try out Machine Translation? That not only are there multiple methods, but all of them give way to enabling your team to form even more accurate translations based on accurate, algorithmic developer customization.

 2. Machine Translation requires a lot of time spent manually correcting inaccuracies.

As with any other translation method, there are of course both advantages and disadvantages to Machine Translation. However, the perception that Machine Translation produces inaccurate translations resulting in more time and resources spent making corrections is, well, inaccurate. Of course, one major challenge is accounting for local context that would make translations more accurate, the truth of the matter is that now the most effective MT use cases actually balance out this challenge by adding a “human-in-the-loop” aspect to the overall MT process.

This, as the term suggests, brings a human translator into the overall workflow. By combining machine and human, the synergist result is more optimized, faster, and accurate translations.

3. Machine Translation means no more human translators on the job.

Following the previous misconception, this one is naturally debunked. While Machine Translation as a standalone method and algorithm has its advantages in terms of efficiency and accuracy, there is still no replacing the human translation touch. Because at the core of it, localization is a human-centric process that aims to help improve communication — communication of your global business brand, and communication between your representatives and your customers.

Localization is an investment made by companies and their global growth teams to be able to connect and communicate with humans on the other side of the world who are speaking different language, and this naturally means the need to be cognizant of cultural nuances in speech and overall language. As a result, translators are an essential element that help to humanize the translated content. And with more authentic content at scale, businesses will be able to make more authentic connections at scale.

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This post is one of many in our latest #MachineTranslation series, exploring the pros, cons, and possibilities that MT brings. To learn more, check out the rest of the series and stay tuned for more Machine Translation insights:

• Recent MT Trends, Research, and Features Taking Companies Global
• How Machine Translation is Increasing Accuracy for Asian Markets & Beyond
• Machine Translation: Pros, Cons, and What the Future Holds