Lots of people care, specially in Asia(Chinese and Japanese). It is just that the problem is incredible hard.
We put 5 very smart people working for a year on that, and it was totally impossible meeting people's expectations, specially people like doctors taking notes fast(and ugly).
We thought that the market was in creating mindmaps or something instead as people could write slower and better.
But people write a double u and expect the computer to see an "m". With deep learning is possible but extremely flimsy.
> The program was efficient enough to run in real-time on a IBM System/360 computer, and robust enough to properly identify 90 percent of the symbols drawn by first-time users.
I just want to point out that 90% accuracy is, from a user's point of view, awful handwriting recognition performance. It means you will be correcting on average about 10 words per paragraph! Even 99% percent accuracy is not nearly good enough to give people a sense that the computer is good at handwriting recognition.
I also want to point out the difficulty and danger in interpreting strokes when doing handwriting recognition.
In the last demo box, try writing a capital Y without lifting the pen. You'll have to go "up and down" one or both upper branches. Because of this, the recognizer will call it a K, A, or N even though it is obviously a Y when you're done.
This demo is constrained to only using one stroke per letter, but systems that permit multiple strokes still get into trouble when the strokes don't match what they are expecting--for example if you draw an X using 4 individual strokes outward from a central point.
This also happens with words. In Microsoft's handwriting recognition in Office in the early 2000s, writing the letters of a word out of order completely borked the recognition. For example writing "xample" and then going back and adding an "e" at the beginning would not produce a recognized word of "example."
My point with all of this is that there is a reason you probably don't do all your computing with natural handwriting. It's a surprisingly difficult problem. Users do not expect it to matter how they form letters and words on the page. And they have very low tolerance for correcting computer mistakes.
Arguably, an X drawn this way should NOT be recognized as an X--that's not how an X is spelled.
If the task is communicating with the computer, then recognition of the gesture is a valid approach. Just as there are conventions regarding the spelling of words, there are conventions involved in the formation of letters. Why not use them? It would even seem incorrect to leave these out.
A computer that interprets the behavior of writing, rather than the final symbols, is going to violate user expectations at some point.
Why? Because people do not always write as linearly as you might expect, especially when writing fast. They might drop or mis-write letters or words, then go back and fix it. Or quickly jot down just enough letters to remind themselves of what they heard, then go back and fill the rest in. A routine that interprets actions in order is going to have a hard time with actions that the user completes out of order.
Not that I don't think "meet me halfway" type approaches (like the Graffiti system) aren't worth using, but in this case we're talking about recognizing writing (the artifact), not writing (the verb).
you could also keep multiple interpretation of a word pending (and a text search for all of them would take you there) and eventually ask the user to disambiguate if the user wants to. I assume this would be an acceptable solution for non dictionary words too...
Wait, what? Doesn't that imply that a paragraph needs to have 100 words in it, in order for 10 of them to be recognized wrong at 90% success rate? That seems super-long, anyway.
My stats are really rusty, perhaps that's just one of those unintuitive cases that confuse people like me.
For reference, the above paragraph is 78 words long.
That is to say, people have a higher tolerance for things that are within expected norms of their environment. Ideally, we want no corrections. But, having to do them constantly for a time will quickly desensitize people to this. (And yes, this is currently just an assertion of mine, I don't have data backing it. Just some anecdotes.)
I hadn't considered that it was intended to act as a warning that the content might be more error-prone.
Edit: I think where the Afterword says "inputting text with a stylus is likely slower than touch typing", they're forgetting that we still don't have a really acceptable way of inputting text on mobile devices. Swype and its ilk are close, but still hamfisted at times.
Reality check: Our machines do not yet accurately manage simple reading tasks.
It was (yay!) published as recognit.bas (VB) and I'd be really happy if someone still has a copy.
It recognized just numbers but the basis of operation was similar to the linked article.
