Translating is difficult work, the more so the further two languages are from one another. French to Spanish? Not a problem. Ancient Greek to Esperanto? Considerably harder. But sign language is a unique case, and translating it uniquely difficult, because it is fundamentally different from spoken and written languages. All the same, SignAll has been working hard for years to make accurate, real-time machine translation of ASL a reality.
One would think that with all the advances in AI and computer vision happening right now, a problem as interesting and beneficial to solve as this would be under siege by the best of the best. Even thinking about it from a cynical market-expansion point of view, an Echo or TV that understands sign language could attract millions of new (and very thankful) customers.
Unfortunately, that doesn’t seem to be the case — which leaves it to small companies like Budapest-based SignAll to do the hard work that benefits this underserved group. And it turns out that translating sign language in real time is even more complicated than it sounds.
CEO Zsolt Robotka and chief R&D officer Márton Kajtár were exhibiting this year at CES, where I talked with them about the company, the challenges they were taking on and how they expect the field to evolve. (I’m glad to see the company was also at Disrupt SF in 2016, though I missed them then.)
Perhaps the most interesting thing to me about the whole business is how interesting and complex the problem is that they are attempting to solve.
“It’s multi-channel communication; it’s really not just about shapes or hand movements,” explained Robotka. “If you really want to translate sign language, you need to track the entire upper body and facial expressions — that makes the computer vision part very challenging.”
Right off the bat that’s a difficult ask, since that’s a huge volume in which to track subtle movement. The setup right now uses a Kinect 2 more or less at center and three RGB cameras positioned a foot or two out. The system must reconfigure itself for each new user, since just as everyone speaks a bit differently, all ASL users sign differently.
“We need this complex configuration because then we can work around the lack of resolution, both time and spatial (i.e. refresh rate and number of pixels), by having different points of view,” said Kajtár. “You can have quite complex finger configurations, and the traditional methods of skeletonizing the hand don’t work because they occlude each other. So we’re using the side cameras to resolve occlusion.”
As if that wasn’t enough, facial expressions and slight variations in gestures also inform what is being said, for example adding emotion or indicating a direction. And then there’s the fact that sign language is fundamentally different from English or any other common spoken language. This isn’t transcription — it’s full-on translation.
“The nature of the language is continuous signing. That makes it hard to tell when one sign ends and another begins,” Robotka said. “But it’s also a very different language; you can’t translate word by word, recognizing them from a vocabulary.”
SignAll’s system works with complete sentences, not just individual words presented sequentially. A system that just takes down and translates one sign after another (limited versions of which exist) would be liable to creating misinterpretations or overly simplistic representations of what was said. While that might be fine for simple things like asking directions, real meaningful communication has layers of complexity that must be detected and accurately reproduced.
Somewhere between those two options is what SignAll is targeting for its first public pilot of the system, at Gallaudet University. This Washington, D.C. school for the deaf is renovating its welcome center, and SignAll will be installing a translation booth there so that hearing people can interact with deaf staff there.
Continue onto TechCrunch to read the complete article.