When it comes to choosing an MT engine, there is no perfect answer. The final choice of the MT engine can come down to several possible factors. For example, some MT engines produce better results for a specific language pair or if equally capable, results might be affected by the topic.
Some companies publish detailed analysis of MT output and rank engines for some language pairs. One such company is inten.to and they post some results on a regular basis. The latest study is available here.
Studies like this one might give some insights into what engine is better for some language pair. But when dealing with a large project, it might make sense to perform testing using different MT engines and collect feedback from the translation teams. The perception from translators might vary from the automated results generated for the studies. Testing a couple of thousand words with selected engines should be sufficient in most cases.
Fortunately, Smartcat makes it easy to perform such a test. In any project, it is possible to assign multiple MT engines per language. The results will be displayed in the editor and the translators will be able to indicate which MT engine they perceived to produce the most usable output. When setting up a project, simply click on the settings wheel for MT at the Settings stage:
As you can see, there are two options for machine translation at that stage — a free MT option and paid services. The free MT version is provided by Yandex but in exchange for free MT, they collect post-editing data used to improve the engine. This could be a consideration when working with sensitive documents. The paid services are provided by different MT developers under commercial licenses with varying terms of services. You can buy MT services on the Productivity Services page that is accessible from the left side main menu.
In either case, when you click on the settings wheel, you will be able to select MT engines for individual languages:
In the screenshot above, you can see that it is possible to select a different engine for each language. Simply drag and drop the language label to the MT engine you want to use for that language. By clicking on the Add option, you can add languages to a specific engine. For example, you can see that French will be processed by two different engines above.
Some engines do not provide output for all languages. When you drag a language label to a different box, some boxes will become unavailable if there is no coverage from these engines.
Note: Using multiple engines can be useful for testing but is not practical for production. First, it adds to the cost of production as most engines are paid services and second, it might negatively affect the linguist's productivity as they might spend more time evaluating the MT output than editing it.
The MT output can be used to pre-populate the target segments in the editor using the pre-translation option in the case of a post-editing project or simply offered as a suggestion to the linguist along with matches from the translation memory and glossary terms in more traditional projects.
This concludes Section 3 of the onboarding process. In Section 4, we will focus on project management features.