Today’s Translation Management Systems (TMS) are usually equipped with a variety of connectors for the integration of Machine Translation Systems (MT systems). More and more systems, like Google AutoML, are now enabling users to train engines with their own language data.
With an increasing number of user-specific engines in various languages and specialist areas (domains), the TMS, connector and machine translation system need to work together smoothly to enable flexible integration of the engines.
Today’s installment of our blog series showcases this integration process via the example of the cloud-based MT system KantanMT and the TMS Across. First, we will discuss the MT System KantanMT and then go on to explain how it is integrated into the translation process within Across.