From Early Steps to Global Impact: The Power and Promise of Neural Machine Translation

Did you know that neural machine translation (NMT) was a byproduct of the Cold War?

Besides the famous Georgetown-IBM experiment, machine translation was used to develop SYSTRAN, the first large-scale machine translation system of its kind. The U.S. Air Force relied on it to translate Russian documents during the Cold War. Then, it became a crucial tool for the European Commission to communicate with each other in multiple languages.

It became clear very quickly just how practical this technology was. So machine translation, which was famously clunky, awkward, and inaccurate in the beginning, evolved into the incredible neural machine translation (NMT) systems we have today.

And if you run a business, using neural machine translation to translate your website is a smart strategy for reaching new markets, optimizing your website for multilingual searches, increasing international sales—and ultimately, growing your business.

While neural machine translation can sound complex, leveraging it for website translation can be surprisingly simple. What’s the secret?

Read on as we explore how neural machine translation came into being and provide a beginner-friendly explanation of how it works. We’ll also shed light on how you can use it to translate your website without needing first to obtain a Ph.D. in machine translation!

What is Neural Machine Translation?

To explain what neural machine translation is, we need first to understand machine translation (MT).

Simply put, machine translation is the process of using computer software to translate text from one language to another. Feed your input sentence to the machine translation software, and it will automatically generate translated text in your target language. No human involvement needed.

Machine translation is used in all sorts of ways, such as:

• Localization of software applications by developers.
• Translation of website copy into multiple languages to cater to a global audience.
• Translation of subtitles for television and movie consumers.
• Translation of patent documents before filing them with patent offices worldwide.

Machine translation techniques have evolved over time, with neural machine translation being the latest and greatest version of the technology. Unlike traditional machine translation, neural machine translation uses artificial neural networks to translate text.

In short, it uses deep learning technology to not only translate text but also improve the accuracy of its translations over time. It’s no wonder that it is one of the most accurate translation technologies on the market today.

Don’t worry if this sounds confusing. Next, we have a quick history lesson on the development of neural machine translation and an explanation of how this advanced technology works.

How Was Neural Machine Translation Developed?

Rule-based Machine Translation

The earliest form of machine translation was rule-based. This is the kind of technology SYSTRAN used so that American airmen could understand Russian technical documents.

Such software would analyze the source text word for word and then refer to a set of rules developed by linguists to decide how to translate each word from the source language to the target language. These rules included word order, word structure, semantic rules, and so on.

But translating words one by one using such a crude system didn’t give rise to the most accurate translations. It worked well enough for simple, direct sentences, but it struggled with ambiguity, idioms, and complex sentence structures.

In this regard, statistical machine translation (SMT) models—the next evolution in machine translation—did somewhat better.

Statistical Machine Translation

Statistical machine translation software would first crawl through massive datasets of human-translated texts (also known as bilingual text corpora). Then, it would use frequency-based statistics to decide on what would most probably be the most accurate translation.

While much more advanced than its predecessor, it still came with some drawbacks. Since it operated primarily from probability and produced sentences in fragments instead of considering the entire meaning, its output was often disjointed and unnatural-sounding. It had the same struggles in understanding nuances and ambiguity, requiring more corrections. ​​

Such technology has improved over time, essentially growing into state-of-the-art neural machine translation that we know and heavily use today. In the next section, we’ll cover how neural machine translation works in more detail.

How Does Neural Machine Translation Work?

So what makes neural machine translation different? Without getting too technical, neural machine translation uses deep learning techniques and artificial intelligence to:

• Analyze the source sentence and
• Find patterns for generating a suitable translation in the destination language.

This technology is based on deep neural networks, an interconnected series of neurons or “nodes” modeled after the human brain. One example would be recurrent neural networks, or RNNs, which may use an encoder-decoder architecture with an attention mechanism.

Before being deployed for translation, the neural MT software will be given training data in the form of different examples of translations for a certain text. Using such data, the software is then “trained” to produce the most accurate translation for a particular situation.

Unlike rule-based or statistical machine translation, neural machine translation systems consider the entire sentence as a whole rather than chopping it up into fragments. Because of this, it was better suited to capturing nuances and more complex sentences, therefore producing more fluent output.

What Makes Neural Machine Translation Better Than Other Translation Techniques?

Neural machine translation has many advantages over traditional machine translation. These include:

Higher Translation Accuracy

Previous traditional machine translation methods weren’t sophisticated enough to translate certain, especially complex languages. The resulting translations were so poor that they were practically unusable without first undergoing major manual revisions by humans.

However, with their capability to “learn” over time, NMT systems constantly improve the quality of their translations. Traditional machine translation systems couldn’t do this since they had no function for “self-learning” and adapting their translation output over time.

Accordingly, when sufficiently trained, neural machine translation software can produce much more accurate translations than their traditional counterparts.

For example, Google previously found that its Google Neural Machine Translation (GNMT) system reduced translation errors by about 60% compared to its phrase-based production system.

Similarly, we conducted a study on the usability of machine translation for website translation needs. After reviewing the quality of website translations produced by various leading NMT technologies, we found these translations to be highly usable and require, at most, minor editing.

The neural machine translation technologies also particularly excelled in translating German, generating the most segments of “no-touch” translated text (that is to say, they did not require manual editing).

Less Need For Human Input

After the source text undergoes a first pass of machine translation, it usually undergoes further human refinement to ensure its accuracy and suitability for the target audience.

The higher translation accuracy provided by neural machine translation means that the resulting translations need less manual adjustment (also known as “post-editing”) before being ready for use.

Quicker Translation Turnaround Times

When businesses can obtain more accurate machine translations that require less post-editing, they can start making use of the translations sooner.

But apart from that, it’s possible to train neural machine translation models within a short period of time. This, in turn, allows for speedier translation processes.

For example, Facebook uses neural machine translation to translate text in posts and comments. As you probably know, there are a lot of such content on its platform. While the business previously needed almost 24 hours to train its neural machine translation models, it was able to cut this timeframe to just 32 minutes!

Can You Apply Neural Machine Translation To Your Business And How?

Using neural machine translation to translate your website may sound intimidating, requiring a costly investment into new tech and research and development. This is not true!

Nowadays, there are many pre-built NMT tools available in the market to help you translate your website content into various languages. These tools are also quite affordably priced. In fact, they tend to be cheaper than engaging a professional human translator to translate your website in its entirety.

So what are some examples of where neural machine translation could be useful for your business?

Customer Support

The quality of your customer support could make or break your business. But unless you have hundreds of customer support agents on your team, there’s a big chance that you don’t speak the same language as some of your customers.

Fortunately, this is easier to solve these days, thanks to NMT. Integrating multilingual chatbots into your support workflow allows you to give instant assistance to your users, especially for frequently asked questions.

It can also be very useful for answering simple customer queries by email, instantly giving your support team multilingual capabilities.

Product Listings

If you run an ecommerce store, what better way to reach your international audience than by translating it?

Translating the entire checkout process—including your product descriptions, currencies and measurements used, the cart page, all the way until the order confirmation—will immediately open up your store to the world.

Even better, that means you can have an international store up and running in a few days depending on the tool you use. (Hint: Weglot can do this in minutes!) With NMT, you’ll have faster market entry without having to assemble a team in your target country (at least, not right away.)

Social Proof

One of the biggest weapons in your arsenal for conversion? Social proof.

Touting the benefits of your business simply won’t do it anymore in this day and age. Customers need proof that you’re what they say you are.

And while having social proof in your website’s original language can be powerful, what will certainly take things up a notch is translating it. That way, users of different languages can understand the impact your product had on your customers, especially if they had the same pain points as you do.

Translating Your Site With Neural Machine Translation

Our Weglot website translation and localization solution is an end-to-end tool designed to make going multilingual easy.

We use a proprietary mix of NMT translations from leading machine translation providers DeepL, Microsoft Translator, and Google Translate to instantly generate translations that are higher in quality compared to using these machine translation technologies on their own.

We support the translation of over 110 languages, from common ones like English, German, Spanish, and Italian to less common languages such as Tatar and Malagasy. We also offer users the option to add custom languages like Brazilian Portuguese or Canadian French.

Weglot also does more than just text translation. Among other features, it can:

• Translate images and videos: Weglot provides a built-in media translation feature for displaying different images and videos to audiences from different countries. It lets you specify alternative media URLs for different language versions of your website content. You’ll find this feature especially handy when your media contains wording or needs to be swapped out to fit the local context.
• Facilitate team collaboration: Weglot makes it easy for your staff members or external translation agencies to review your translations. All your translations are stored in the centralized Weglot Dashboard. You can add collaborators by their email addresses to grant them access to your translation project. You can also adjust their access permissions anytime as required. You’re in complete control.
• Optimize your website for multilingual searches: Multilingual search engine optimization (SEO) refers to the steps taken to enhance your website’s visibility in multilingual search engine results. It’s an essential process if you’re building your website with a global audience in mind. With features such as automatic hreflang tag implementation and metadata translation, Weglot will help set your website up for success in the multilingual search arena.

Weglot offers no-code integrations with leading website platforms such as WordPress, Webflow, and Shopify. It’s easy to set up and can help your business do the following:

• Save money: Weglot connects with leading MT providers to provide a first pass of machine translation of your website content. If needed, you can then use professional translation services to look over and adjust certain key translations before you use them on your website. This language translation strategy can save you a lot of money compared to having a professional translator translate all your website content from scratch.
• Save time: Manually translating text word for word not only leaves room for human error but is also very slow. Weglot translates and displays the whole of your website instantly, helping you make your website multilingual in minutes and improving your website translation project workflow tenfold.
• Translation quality: As mentioned, Weglot uses a proprietary mix of neural machine-learning translations to enhance translation accuracy. This certainly beats translating text independently—especially if you aren’t a skilled linguist in the relevant language pair. You then get complete editing control over your translations so you only display the translation quality you want on your site.

More than 110,000 websites use Weglot for their translation needs, with outstanding results.

French eyewear brand Jimmy Fairly is one of them: the business doubled its percentage of international sales just one week after using Weglot to translate its French website into English. Encouraged by these results, Jimmy Fairly subsequently translated its website to German and Italian as well and reaped an overall 70% increase in web sessions after eight months.

Use the Power Of Neural Machine Translation For Your Business With Weglot

Delivering superior translation performance, neural machine translation is a significant improvement over other traditional machine translation techniques. With that in mind, it’s unsurprising that NMT is the machine translation technology of choice for so much of the business world.

As our machine translation study reveals, the volume of machine-translated web content has increased sixfold over the last two years. Machine translation is also used for large projects, with more than 10% of translated websites containing over 50,000 words. Finally, only about 30% of machine-translated content is edited, suggesting that a significant portion of machine translations is so accurate that it requires no further refinement.

Weglot makes it easy to harness the power of NMT to translate your website content. It’s simple to set up and automatically chooses the most suitable machine translation engine to produce the best translation for any given language pair. The result is speedy, high-quality website translations that you can implement without fuss. Just take it from Corrine Ellsworth-Beaumont, the CEO of Know Your Lemons Foundation:

“With Weglot we were able to translate a number of pages into 10 different languages within the first week of the website launch, dramatically increasing our international visibility.”

If you’re keen to experience the power of Weglot for yourself, you can sign up for a 10-day free trial here.