Machine learning is one of those things. It’s reshaping our world in ways that we never thought possible. We are on the cusp of a new era where machines will learn and evolve at an accelerating pace. It’s up to us to decide how to use this power.
The future is machine learning. What will you do with it?
Researchers have used hybrid machine translation processes to address issues with traditional approaches. By combining rules-based machine translation with statistical methods, they’ve increased reliability and bolivia mobile database accuracy. Back then, hybrid machine translation referred to combining two or more machine translation approaches into one system.
However, innovators in the language and technology sectors have now assigned another definition to hybrid translation. Human translation + Machine translation.
What Is Hybrid Machine Translation?
Hybrid machine translation is a process that combines both human post-editing and machine translation methods, such as statistical generation and neural machine translation. This system creates one efficient workflow and accentuates the strengths of both machine translation and human translation.
Human-machine translation produces more accurate and nuanced results than either method could achieve on its own. Many leading companies are already using hybrid translation to expand their market reach to a global level. Experts around the world point to it as the future of translation.