On desktop, I use the AI-designed Halmak Keyboard, and its had great results.
Rather than manually picking letter positions, Halmak was designed by an evolutionary algorithm, based on a given set of criteria, and sample text.
I designed the original english thumb-key layout manually, with trial-and-error, and based essentially on 3 criteria:
- Letter frequency
- Alternating thumbs
- Thumbs come from the bottom corners, so lower and edge tiles are easier than higher.
But I did not take into account things like digrams / trigrams, and I don’t know enough about evolutionary algorithms to do it.
Would anyone be interested in tackling this problem?
I’d be willing to give it a try. Have you done any work on the hand movement model, like he shows at 2:06 in the video you posted? Mine would be different from yours, since I type with just one thumb.
The important part is how much time it takes to type key 1 after typing key 2, right? Maybe just logs of people typing with time stamps for every key or something? Then I could make a map to teach the AI with.
Are you particularly attached to the evolutionary algorithm? I might try a few different ones.
Oh it looks like MessagEase has. I should’ve looked at their paper first.
MessageEase unfortunately didn’t do any optimization after their first 9 letters ( and I don’t fully trust what they did there either ). When it came to the swipes, they based it off of whether the letter was curly-shaped or not (curly shaped letters go off the center key)
@Dessalines where did this end up? I have experience with genetic / evolutionary and similarly applicable optimization algorithms and would be interested in helping to optimize the layout.