Few doubt that machine translation can boost productivity. However, most LSPs have yet to fully adopt it. David Canek of MemSource Technologies gives a step-by-step tutorial selecting the right MT technology, measuring MT quality at the segment level, and applying a pricing model that will reflect the translator’s actual post-editing effort. Introducing machine translation into an LSP’s translation workflow may seem like a daunting task. It involves getting new technology, modifying the existing workflows, reconciling machine translation with translation memory and last but not least, devising post-editing rates that will distribute the benefits of machine translation between the LSP and its translators in a fair and transparent way. MemSource has gone a long way to make machine translation adoption for LSPs as easy as possible. It treats machine translation as a gigantic translation memory and extends the established translation memory analysis and discount schemes to machine translation. All of this is neatly integrated in MemSource Cloud and MemSource Server software. It will take you literally minutes to get up and running in MemSource Cloud and experience the seamless integration of machine translation in the MemSource cloud-based CAT environment.
David Canek is the founder and CEO of MemSource Technologies, a software company providing translation technology based in Prague, the Czech Republic. David, a graduate in Translation and Comparative Studies, received his education at Charles University, Prague, Humboldt University in Berlin and the University of Vienna. His professional experience includes business development and product management roles in the software and translation industries. David has delivered a number of presentations on innovation and trends in the translation industry, including the growing use of machine translation post-editing and cloud translation software.