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Machine Translation (MT) has been around for decades. In recent years, it has evolved at an exponential rate. As companies produce ever-growing amounts of content in different languages, they have come to see MT as an opportunity to extend their reach in an increasingly globalized world.
Companies seeking to deploy MT can explore the following four basic strategies.
No matter which strategy you are contemplating, selecting the right engine may be challenging without the proper data and MT experience. Lionbridge is an expert in MT. In addition to having more than two decades of MT experience, we have gathered a large volume of linguistic and quality data about MT technology that will help you make the right choice. This webpage provides basic information about the performance of popular MT engines for the most common language pairs to help you select the best option based on your content.
When choosing among the many available MT systems, it’s important to note some engines address a specific function or domain. If your needs don’t align with that purpose, the engine may perform sub-optimally no matter how advanced it is. To determine the best option, first, identify why you are using MT.
If you want an MT engine for general use, it may be appropriate to use Google Translate or Bing Translator. If you seek MT services for a specific language or domain, you may achieve better results by turning to Amazon Translate or DeepL Translator.
Lionbridge’s Machine Translation Tracker analyzes engine performance monthly to help you figure out the best MT engine depending on the language pairs you use. The next time you ask which MT engine is best, reframe the question to, “Which MT engine is best for me?” And count on Lionbridge for guidance.
Want to learn more about the different types of MT technologies? Check out our blog Machine Translation in Translation.
If you’ve been following these pages, you’re familiar with our generic MT comparative evaluations. Each month, we identify which MT engines are performing best for given language pairs and track engine improvements. In March, the performance of the different MT engines was flat. It’s a trend we’ve been noticing for some time already. As we commented last month, it may indicate that a new MT paradigm is needed.
While we share generic results, companies are increasingly pursuing custom MT comparative evaluations. Unlike the generic version, these evaluations take a company’s specific needs into consideration when determining the most advantageous MT engines.
When a company wants to start using MT or improve the way it currently uses MT, it is critical to identify which MT engines will work best. When we execute custom evaluations, we take a similar approach to the one demonstrated on this page, but we make recommendations based on a company’s content type and language pair requirements.
While custom MT comparative evaluations have been available for years, there’s greater demand for them. We attribute this trend to the important role MT plays in helping companies succeed in a digital marketplace.
—Rafa Moral, Lionbridge Vice President, Innovation
For more insights and future trends about Machine Translation, read our Future of Language Tech blog post – Future of Machine Translation.
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