Some have taken the notion of QA assurance further by combining machine translation systems with machine post-editing services. This hybrid machine translation workflow results in superior quality and accounts for rare word misinterpretations.
Recently, TechBullion interviewed Maya Ronen, the Chief Operating Officer of Tomedes, one of the top language service providers specializing in localization with a certification in Machine Post-Editing. She highlighted the need for hybrid systems featuring skilled human translators.
“If there’s no human involved in the process, it causes problems. If no one checks it or reviews it, that’s where you see problems in translation arise. This is why it’s best to have humans involved before and throughout the process,” she said.
The future of SMT is uncertain as NMT continues hungary mobile database to gain popularity and show strong results. Some of its guiding principles may prove useful to NMT. However, SMT still has its advantages and may continue to be used in some domains or for specific language pairs. Ultimately, you’ll have to decide which approach fits your needs depending on each project's specific needs and goals.
One thing is for sure. The future of machine translation is vibrant, showcasing the abilities of AI and human ingenuity at the highest level.
Everything You Need To Know About Neural Machine Translation
Everything You Need To Know About Neural Machine Translation
Neural machine translation (NMT) is already radically changing industries around the globe, and it’s just getting started. Currently, neural translation systems produce more accurate translations than traditional machine methods. Plus, they sound much more natural and human.