Technology

Now is an exciting time for media localization, with technologies improving across the board making automated subtitling and dubbing an actual possibility. With machine dubbing, we're still far from having automated voices that sound like real human actors expressing emotions and delivering high-quality acting performances.

One year ago, we called the VIT hype a solution without a problem. In times of COVID-19 it has now become the solution to the problem. We figured this might be a good time to clarify the difference between some remote interpreting acronyms that easily get mixed up: VIT, VRI, OPI, and RSI.

In this webinar co-hosted by Nimdzi and Xillio, we look at technology around localization and connectivity.

Continuous growth and fragmentation have been the key characteristics of the language services market. Let's see what the data says.

Because of the speed with which UGC (comments, feedback, reviews) is being created and the corresponding costs of its professional translation, many organizations turn to MT.

Judging by the conversations Nimdzi has been having with users of translation business management systems (BMS), the time for a change is now.

Every once in a while, people outside of the localization industry join events dedicated to the language business. We've heard them say we're a nice bunch of people, enthusiastic about our jobs. This feeling surrounding our industry was confirmed once again at MESA’s Content Workflow Management forum in London on 26 February.

Competition is fierce in the Translation Management System (TMS) arena, with dozens of providers duking it out to win over clients.

Is it possible to auto-select the best MT Engine? Let's take a look at what's out there.

One of the main reasons for implementing machine translation (MT) into localization workflows is that it saves money. And time. This time, let’s focus on money. In particular, cost savings.