Does Your Company Need a Custom-Trained Machine Translation Model?
For companies that often deal with bilingual or multilingual clientele, translation is a necessary part of business that’s traditionally been done by human translators. With the rise of machine translation solutions in recent years, however, industries across the globe are eager to adopt this new way of handling large volumes of translations much faster than ever before possible.
As with most technologies, machine translation engines come in various shapes and sizes, and not all of them are created equal. Whether you frequently use machine translation in your business or you’re completely new to the game, there are a few things to know about both the benefits and shortcomings of readily available machine translation solutions. Read on to discover what machine translation can do for you—and why a custom-trained model may be the perfect fit for your business.
What is Machine Translation?
For those who may be unfamiliar with the term, the best-known and most commonly used machine translation engine is Google Translate, where users can input source text in a variety of languages and translate it into a target language of their choice.
One of the biggest benefits of MT is that it can be used to translate large volumes of copy in a matter of seconds.
What’s the Difference Between Google Translate and a Custom Machine Translation Engine?
With Google Translate readily available for anyone on the internet to use, you may be wondering why there would even be a need for custom machine translation engines.
For one thing, translations done with generic MT engines (such as Google Translate) are crowdsourced, meaning anyone—not just native speakers and specialists in industry terms—can recommend a translation. Since it’s crowdsourced, Google Translate also doesn’t translate every language pair with an equal level of quality and often doesn’t account for different dialects within a language. The free MT engine is also quite literal with its translations, and it doesn’t do too well picking up the tone, mood, or other subtle nuances that make up language.
For this reason, business translations done with Google Translate tend to be rather low-quality, often full of grammatical and syntax errors. What’s more, depending on the language or the context—for instance, in the case of technical fields like science and medicine—the translation auto-generated by the MT engine can be outright wrong. Translations done with these systems almost always require extensive post-editing from a specialized editor or, at the very least, “cleaning up” by a native speaker.
Another major concern with crowdsourced MT engines like Google Translate is that they have serious privacy concerns, with a potential risk for hackers to access any sensitive information people may have chosen to translate with these tools.
By contrast, custom machine translation engines are trained using large volumes of sentence pairs that have already been accurately translated and reviewed by an editor or native speaker. When it comes to building custom-trained MT engines, it’s important that the sentences used to train the model include any specialized terminology or other industry-specific information that will show up in the company’s texts again and again. The more detailed and error-proofed the data input into the custom MT engine, the higher-quality translations it will yield.
The Benefits of Custom Machine Translation Engines
As mentioned earlier, one of the greatest advantages of MT is that it can handle a large volume of work in a fraction of the time it would take a human translator to complete. Here are just a few more benefits of custom MT engines:
1- Faster translation delivery
With Custom MT engines, you can significantly reduce the need for Machine Translation Post Editing, as they are built using industry-specific data. The result is translations that are much more accurate—which, in turn, saves companies both time and money in the review and editing process.
2- Consistency in translations
Another key benefit of custom-trained MT engines is consistency. Using CAT tools that store certain terminologies or syntax choices in the system is a foolproof way of ensuring that those stylistic choices are retained throughout a body of text, or even across different groups of texts. Not only that, but for many companies, custom MT engines also ensure consistency over time—as a scalable translation solution that’s independent of the company’s HR processes, a custom MT engine will continue to deliver high-quality results regardless of changes to the company’s staff or the volume of translations needed.
3- Improved data protection
Last but certainly not least, custom MT engines are much more secure than generic MT engines, which are crowdsourced and store your data and use it to improve the models. For companies or enterprises that deal with sensitive information in need of translation, this could pose a potential risk in terms of data security—making custom MT engines a wise (and even necessary) investment for said companies’ long-term success.
Who is Custom-Trained Machine Translation For?
For companies that have traditionally worked with human translators, the question of when to use machine translation can be a tricky one to answer. In general, a custom MT solution is recommended for companies that have at least one in-house translator (or a team of translators), or for businesses that regularly find themselves having to outsource translation work. Custom MT engines are ideal for businesses operating in industries with very specific terminology—such as those in the legal, health and medicine, or e-commerce fields—as they provide a level of accuracy that generic MT solutions simply can’t match.
Custom MT engines are also the right choice for businesses that deal with customer information and other sensitive data, as they provide a necessary level of security.
Companies that already have a wealth of bilingual sentence pairs are prime candidates for developing their custom MT solution, as this archive of accurately translated data can be used to train and improve the MT model.
How Much Training Data is Required?
Although there isn’t an exact number of bilingual sentence pairs required to build a custom MT engine, experts recommend having hundreds of thousands or millions of sentence pairs related to the specific industry to ensure the utmost accuracy in translation. The more data you have to train the model, the better the results of the MT model will initially be. However, as you use your MT model, your new translations get constantly fed into the machine, resulting in an improved model (and results) over time.
If you’re a business looking to expand your audience reach and streamline your translation processes via MT, check out Tarjama to get started. Built on the latest neural deep-learning models, Tarjama’s Machine Translation engine relies on high-quality business data pre-approved by human linguists—so whether you choose Tarjama’s existing MT solution or opt for a custom-trained MT model for your business, you can rest assured that your translations will turn out accurate and error-free each time.