Computer science terms once exclusively used in scientific communities have become ubiquitously integrated into our daily lives—the news we read, products we consume, and the technology we use. Some are used interchangeably with one another (incorrectly), others are hazy in definition and application. In light of this, we thought we’d lend clarity to the top Machine Translation (MT) related computer science terms you may encounter.
Translation is a complex art form – one we highly respect. The manual process involved makes it difficult to keep up with changing technology and progressive business practices. Modernizing seems formidable. Change breeds uncertainty. It’s understandable for localization teams to stick with legacy vendors, a static stack, and the same workflows.
We’re pleased to announce a new feature in our interface that improves the translation review process. Previously, reviewers could make general text comments about errors and introduce categories by using hashtags to indicate the type of error (such as #punctuation or #mistranslation). However, it was still a manual process to collect the different hashtags and identify precisely where the error occurred.
There’s little we love more than helping our customers succeed, and providing real value in their localization efforts.
We had the pleasure of joining the SF Globalization meetup this past Wednesday, Feb. 13, at the Autodesk Gallery in San Francisco, where our CEO Spence Green gave a presentation on recent advancements in neural machine translation.
Creating an ROI model for localization is a pain point for many organizations. We’re dedicated to helping solve this problem and have written a complete guide on the very issue. You can get your free copy here. First, we wanted to spend some time dissecting the complications of localization and ROI.
Tech debt — a trade-off of short term gains from shipping quick software fixes in place of better, longer-term solutions — is a common and often unavoidable practice for development teams. Accumulating tech debt provides the ability to resolve problems affecting user experience and software performance quickly.
Many discussions are happening in the localization community, particularly surrounding themes of changing landscapes and workflows, and advancements in machine translation (MT). We find it all very exciting.
If you're beginning to research localization, you'll soon discover it's a highly specialized industry, complete with its own vernacular. That's not to say it isn't accessible or welcoming. One goal of translation, after all, is to break down barriers of communication - not create them.
