Earlier quoted context omitted.
Actually I think most of the work has been done in academia --- certainly that's where the recent deep learning stuff has come from. So, I don't think the important stuff is patented. (In general it's very hard to lock down ML improvements under patent. Once we can do it one way, and understand a little bit about what's working, we can usually replicate that performance with another technique.) The big problem for op…
First, these are two different problems to solve. Voice recognition and deep learning are different fields. Is training really the issue for voice recognition? It has been a problem that has almost been solved for over a decade. Last year I saw this impressive use of Dragon Naturally Speaking for the PC, running in a VM on a Mac, that pretty much worked to code by voice. https://www.youtube.com/watch?v=8SkdfdXWYaI Th…
The system in the video you link is single speaker, closed vocabulary. You need massive training data for multi-speaker, open vocabulary.