A Return on InvestmentRead the Case Study
“With improved terminology consistency and translation quality, Memsource essentially pays for itself.”
The quality of machine translation continues to improve and linguists are increasingly being asked to edit, or post-edit, machine translation output. But the quality of MT still varies considerably, depending on various factors, including content type and language pairs. Linguists have to sift their way through a lot of low-quality machine translation, occasionally
coming across something that only requires a bit of editing or none at all. This wastes a lot of time.
We know that linguists are saving time with quality scores for translation memory matches, so why not provide the same for machine translation. This is where our AI team came in.