Everything Translation
Everything Translation

AI & Language Translation: How to Train Your Machine Translation Engine

For many years, businesses have depended on human linguists to deliver reliable translations. However, the advent of machine learning engines has made it possible for just about every company to access translation services at lower costs. 

That being said, machine learning for translation applications hasn’t always been particularly reliable, although it’s certainly improving in that regard. Ultimately, reduced costs and expedited delivery can come at the expense of quality. 

Many businesses have accepted this as inevitable, but second-rate translations aren’t a compromise you need to accept indefinitely. In fact, the prospects for translation and machine learning, as well as AI’s role in shaping the future of translation, are far more exciting than you might think. 

What correlation exists between machine learning and language translation?

Many businesses turn to artificial intelligence to speed up processes and save money. Language translation is one area where AI is consistently being utilized. 

Machine learning and language translation are making it possible for businesses to expand internationally and for brands to reach untapped foreign markets. By learning machine translation applications, even small businesses can start thinking with an enterprise mindset. 

How machine learning can save you time and money in content translation

Machine learning, combined with translation memory, can save you considerable time and money when it comes to content creation and translation work. Translation memory is essentially an exhaustive dataset that is constantly updated with business-specific translations. 

A dataset can teach AI to translate segments that are specific to your brand and industry. These segments can be constantly reused, while new segments can be added to an ever-evolving phrasebook to improve consistency and translation quality. 

Both machine learning and translation memory bring instant cost-saving benefits, freeing up budgets that can be allocated elsewhere. Using a translation engine also brings the benefit of consistency. When it comes to branding, there’s nothing worse than inconsistent language. In a worst-case scenario, it can confuse your corporate identity and tarnish your brand authority. There’s also the chance for inconsistent translations to mislead new and existing customers. 

Another huge perk of machine learning is that human translations are free to concentrate on more complex tasks. AI-powered translation engines can automate time-intensive tasks, with human translators free to perform proofreading and post-editing duties. 

The relationship between human linguists and MT engines can be bridged by investing in computer translation courses. The result is that internal deadlines are comfortably met, while external assignments are delivered to clients ahead of time.

The basics of training a machine translation engine

Most translation engines use Google and Microsoft as a framework. However, solutions like Google Translate are fairly limited when it comes to real-world applications. For example, you can’t train MT engines like Google Translate to adapt and evolve to terminology specific to your business. However, with third-party machine translation engines with dynamic machine learning applications, you can. 

Human intervention is crucial for dynamic machine learning. Once an initial draft is translated by an MT engine, human users can then train the application to learn new words and phrases by performing edits. These edits are then stored for future reference, with translation memory constantly improving. The result is that subsequent translations become increasingly reliable. 

Easy ways to improve machine translation quality

Dynamic machine learning and translation memory will play a key role in improving the quality of your machine translations. You can use existing documents as training data to boost translation memory. It’s worth sourcing old documents that have previously been translated into a target language to provide your MT engine with an exhaustive dataset it can use as a point of reference. 

To improve relevance and translation quality, actively edit translations so your MT engine understands the terms and industry-specific language that you use regularly. This should be an ongoing exercise. 

How to make language translation as automated as possible 

As well as using existing documents to bolster translation memory, you can make use of translation engines like Amazon Web Services (AWS). Tools like this allow you to perform ad hoc translations using deep learning systems. Although the results won’t be as reliable as what you can expect from a human linguist, they can come incredibly close. 

To utilize neural networks effectively, however, you will need to invest time and resources into creating glossaries that machine translation engines can use as a reference point. The investment will pay off, resulting in far more reliable translations down the line. 

What kind of content are you looking to translate?

Not all content is a good fit for machine translation. Machine learning lends itself well to by-the-numbers text, but it will struggle with marketing messaging and creative copy. It certainly won’t deliver pitch-perfect results if you’re looking to localize existing content for new markets

Not sure whether to use MT? You can use machine translation if you require rough and ready results for things like document translation, support messages, and internal communications. 

You can also use it to facilitate first-draft translations of e-commerce copy like product descriptions, buying guides, and FAQ sections. However, a more involved text will require some post-editing input from a human translator. 

If you’re working on anything heavy on branding, MT simply isn’t a good fit. Avoid turning to machine translation engines as your big gun if you’re putting together high-value landing pages and homepages, press releases, and SEO content. 

Machine translation engines and confidentiality

How your data is stored and used is important. When using a third-party machine translation engine provider, it’s vital you read the fine print. 

If you’re working with sensitive documents and need to consider confidentiality agreements, any service you use needs to allow you to fulfill your obligations. 

Choosing the right machine translation engine

Ready to embrace machine translation? You’ll need to think carefully when selecting a suitable MT engine. 

Firstly, consider the content you’re looking to translate and the quality levels you’re expecting. You might be looking for basic document translations that don’t require any post-editing input. Alternatively, you might be after translations of literary documents or creative copy. In this scenario, a standard MT engine might not prove sufficient. 

Next, think about the topic of your texts. Some MTs are better suited to translating internal documents and technical manuals, while others are a better fit for the legal sector. Although not as well represented, some MTs are most effective at translating sales and marketing content. If you want to translate more complex texts, it’s always best to go with a neural machine translation engine. 

Language pairs also need to be considered. Common pairs like English and Spanish are well served by affordable MT solutions like DeepL. However, if you need to translate less commonly encountered language pairs, you’ll need to look elsewhere. When working with different target languages, you might find it useful to utilize a combination of several different MT engines. 

For many businesses, deciding on an MT engine will be guided by protecting the bottom line. Even a basic MT can reduce translation costs and turnaround time when working with large volumes of data. However, just because an MT engine can deliver translations quickly, doesn’t mean your overall turnaround time will be reduced. For example, the translated text might require extensive proofreading and post-editing. Spending more on an MT engine that’s tailored to your industry might prove a more cost-effective solution in the long run. 

Machine translation training helps you automate parts of your localization and translation process

Machine translation training is an easy way to automate translation workloads and streamline your localization efforts. If you’re looking for an all-in-one solution with quality, well-trained machine translation, plus professional human linguists with industry expertise, video localization services and more, check out BLEND’s localization solutions.

With the most advanced translation technology and a network of thousands of experienced linguists working in more than 120 languages, we can help your brand become a global powerhouse. Interested in learning more about how BLEND can help you? Get in touch with the team today, and experience the power of our translation technology today.

Curious to learn more on the topic? Read more about the concept of AI translation, AI translation vs. human translation, AI’s impact on language barrier, and transforming translation services with AI. You can also find out more what the top translator tools are, and get inspired by AI-driven MT breakthroughs.

author post

Fouad Habash

As BLEND’s Localization Solutions Engineer, Fouad is a seasoned expert in translation technologies, including TMS, CAT tools, AI and MT. With over 14 years of industry experience, Fouad ensures our clients receive the best and most efficient localization processes.


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