> Because I love swiping, but all my problems with it come from the fact that the QWERTY layout is far from ideal for it. I am 100% willing to learn a new layout if anyone will develop an optimal one for English so that swiping has a 99.9% accuracy rate instead of what currently feels more like 90% or 95%.
90-95% is a very good estimate! That's about what we measure on our test set. I have good news for you, and we will have a blog post about it soon. Because of how our models are built, we are able to optimize for detection accuracy directly by constructing synthetic swipes on each layout for ~50k words, and then testing them through the model. We tested around 800,000 layouts this way.
The biggest issue with QWERTY is that there are far too many words that swipe colinear or obtuse angle letter trigrams. These are both hard to detect and frustrating for swipe users, because you can't clearly indicate the letters you're gesturing. Neural swipe models (at least ours) look for indicators in the gesture pattern that suggests a user was targeting a specific letter, rather than trying to match a gesture shape like algorithmic detection does.
The shape of the keyboard can significantly improve the way the gestures are formed so that there is better indication of letters. The model can still respond to dwell times because unlike shape matching it uses the temporal information. But dwell interrupts flow, and in my opinion should be minimized in swipe layouts.