Google Translate provides its users with a genuine value for their everyday linguistic needs. Nevertheless, the very name of this service has become a synonym of some horrible translations, at least in the Arab World. Most professional linguists are fully aware that receiving a feedback from their clients with “This is Google translated”-like phrases is their worst nightmare. The yet unanswered questions are about the reasons that make machine-translation way behind when it comes to Arabic language, and what Google is doing to enhance this service.

In the crippling agency model in translation project management (see here, here, and here), the role of reviewers (sometimes called editors, or QA Officers) requires some serious rethinking.

During my 10 years of experience in training and learning, and specially while developing my Arabic as a Second Language course over the past three years, my primary goal was to apply Accelerated Learning (AL) methods to all my training programs. However, language learning has its own special requirements that makes creating a special version of AL techniques specific for Language training a necessity. This is where the MAP Technique (Motivate-Anchor-Personalize) fills the gap.

This is the first post in a series of posts dedicated to casting some light on the most important challenges that face the Arabic localization industry. There is no doubt that the Arabic translation sector requires an overhaul, both in quality measures and the business model itself, as manifested by seeing huge multinational corporations who spend millions on communications and PR settle with less-than-mediocre Arabic versions of their documentations, including giant automobile manufacturers, iconic technology companies, huge retailers, and even highly esteemed PR agencies.