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Hmm, since they are having someone imagine writing a character our and using recognition on it, I wonder if there's gains to be had to switching to a simplified writing, like Palm did for their PDAs in the past with Graffiti.[1]

1: https://en.wikipedia.org/wiki/Graffiti_(Palm_OS)




With autocompletion and advanced prediction 90 characters a minute could be effectively much more.

https://www.tabnine.com/


I'd love a neural interface to Dasher, which adaptively learns as you use it which letter combinations are the most popular, and adjusts over time to make it easier and faster to input common text.

It would be wonderful integrated with a context and language sensitive IDE.

https://en.wikipedia.org/wiki/Dasher_(software)

https://github.com/dasher-project

http://www.inference.org.uk/dasher/

>To make the interface efficient, we use the predictions of a language model to determine how much of the world is devoted to each piece of text. Probable pieces of text are given more space, so they are quick and easy to select. Improbable pieces of text (for example, text with spelling mistakes) are given less space, so they are harder to write. The language model learns all the time: if you use a novel word once, it is easier to write next time. [...]

>Imagine a library containing all possible books, ordered alphabetically on a single shelf. Books in which the first letter is "a" are at the left hand side. Books in which the first letter is "z" are at the right. In picture (i) below, the shelf is shown vertically with "left" (a) at the top and "right" (z) at the bottom. The first book in the "a" section reads "aaaaaaaaaaaa..."; somewhere to its right are books that start "all good things must come to an end..."; a tiny bit further to the right are books that start "all good things must come to an enema...". [...]

>.... This is exactly how Dasher works, except for one crucial point: we alter the SIZE of the shelf space devoted to each book in proportion to the probability of the corresponding text. For example, not very many books start with an "x", so we devote less space to "x..." books, and more to the more plausible books, thus making it easier to find books that contain probable text.

The classic Google Tech Talk by the late David MacKay, the inventor of Dasher:

https://www.youtube.com/watch?v=wpOxbesRNBc&ab_channel=Googl...

It's based on the concept of concept of arithmetic coding from information theory.

http://www.inference.org.uk/mackay/dasher/

Ada Majorek, who has ALS, uses it with a Headmouse to program (and worked on developing a new open source version of Dasher) and communicate in multiple languages:

https://www.youtube.com/watch?v=LvHQ83pMLQQ&ab_channel=Dashe...




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