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SELECT LANGUAGE:
As companies produce ever-growing amounts of content in different languages, they seek to extend their reach to the globalized world faster and more cost-efficiently.
At their disposal? Machine Translation (MT) engines and generative AI (GenAI) technology, with each technology playing an important but different role in localization.
Whereas GenAI / Large Language Models (LLMs) are highly suited for assisted post-editing and optimizing localization workflows through automation, MT engines are unsurpassed for initial translation due to their superior speed and cost-effectiveness. Moreover, the quality of MT is generally better than that of LLMs for initial translation, though we are tracking developments closely.
Machine Translation solutions are comprised of the following four basic strategies.
Want to learn more about Machine Translation terminology and the different types of automated translation technologies? Check out our blog, Machine Translation in Translation.
When choosing among the many available automated translation systems, it’s important to note that some MT engines are trained to 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.
Identify why you are using automated translations to determine the most suitable option. If you want an MT engine for general use, it may be appropriate to use Google Translate or Bing Translator. However, you may achieve better results using a different tool when seeking MT services for a specific language or domain.
How does Lionbridge select among the different engines? Our best-of-breed approach utilizes one platform with five engines: Amazon, Bing NMT (Microsoft), DeepL, Google NMT, and Yandex. The platform is accessible via our Smart MT™, Application Programming Interface (API), and our customers’ localization workflows.
We provide the flexible application and customization of MT system selection based on language or use case, using language-specific rules, glossaries, and Do-Not-Translate terminology added directly at the platform level instead of at the engine level.
Our MT solutions cover 115 language pairs for leading global brands.
With over two decades of MT experience, we have gathered a large volume of linguistic and quality data about MT technology.
Lionbridge’s Machine Translation Tracker analyzes the performance of the top five MT engines and several GenAI models. We publish the results periodically to help you understand how these tools perform, depending on the content’s domain and the used language pairs.
Check out our findings below. The results—which are everchanging—can give you an idea of which options are right for you.