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So Markov chains provide a good model for next-symbol probability, and touchscreens are amazingly shonky at working out what you really just typed.  Is anyone using a Markov chain to interpret the raw data from the users fat, mashy finger and determine what they really meant to press?  A second-order chain ought to be enough to pick out half a dozen likely candidate letters, most of which won't be in the area of the press.

Date: 2009-06-03 12:36 pm (UTC)
From: [identity profile] andygates.livejournal.com
Ah, now you're coming close to Dasher and its ilk. As long as the user can learn it easily, that's fine. Users learn finger movements, which is why I think Dasher hasn't conquered the world: -tion and -cion would need to be in predictably similar placed whenever they came up. When it was -tion, -cion and -ting, or -tion and -ting, at most one gram can remain static. There's *thought* required to find the right one, and that makes it worse than touch-typing.

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