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Technology CompaniesAppleQuick look at InkWell and Vista handwriting recognition

Quick look at InkWell and Vista handwriting recognition

I just uploaded a screencast that shows handwriting recognition being performed by Mac’s InkWell technology as well as that provided on Tablet PCs and in Vista. In this video, the demo is all done on an iMac within Firefox. The recognition on the Mac side simply uses InkWell. For the Microsoft side, I used the Silverlight-based SearchTIP I described the other day, which uses server side recognition.

Here’s the video:

The video is a little longer than 8 minutes. Enjoy.

I’ve always wanted to do a side-by-side comparison of InkWell and Microsoft’s handwriting recognition engines. You see so much banter on the Internet about Apple’s handwriting recognition being better or that Microsoft’s doesn’t perform up to expectations. I hope this screencast gives people a better idea of how the two technologies compare. Personally, I believe the Microsoft recognition performs better, but that’s me. Others may have differing opinions. No problem.

A couple things that are worthy of pointing out in the video:

* InkWell handles printed text fairly well and does OK with a little bit of cursive text mixed in. However, when all or most of the letters are cursive, it doesn’t do very well. The Microsoft recognizer wins hands down with cursive handwriting.
* The first generation recognizer from Microsoft didn’t recognize all caps text that well. The new recognizer does much, much better.
* The InkWell recognizer appears to leverage stroke order over spatial relationships between the strokes. The Microsoft recognizer does much better at taking spatial information into account which means you can write letters “out of order.”
* The Microsoft recognizer leverages a word dictionary which is easy enough to add words too, however, if the word is a name or something unusual and the words not in the dictionary, sometimes the recognizer doesn’t get the word right. I’ve found if I print the word carefully, the recognition goes up. Same with InkWell’s handling of proper names–although in practice I seem to be able to write names better with InkWell.
* The Silverlight app used in the screencast doesn’t capture the ink as fast as that captured on a Tablet PC, so the quality isn’t as great. This is particularly noticeable in Safari. Because the screencast was performed on a Mac, the InkWell ink looks a bit smoother, but on a Tablet PC you could say the same thing. Silverlight’s ink is good, but the Tablet PC’s ink is even better.
* Editing gestures are supported by both InkWell and Microsoft’s ink recognition, however, the Write Anywhere feature supports the gestures directly. On a Tablet PC there’s no longer a built-in Write Anywhere feature, although there is programmatic support for gestures as well as Flicks gestures (for window navigation) as well as a correction UI built into the Tablet Input Panel (TIP). Is Write Anywhere better than the TIP? It’s probably a matter of choice. The TIP definitely provides more editing control over the ink. InkWell’s Write Anywhere may seem more natural in a greater variety of apps.
* Both recognizers do well with simple math expressions, however, the Microsoft recognizer can recognize bullet lists, simple shapes, and more. Unfortunately, in this simple demo there isn’t a good way to illustrate this. I’ll have to see if I can come up with a better demo.

You can try out the handwriting recognition yourself–even if you don’t have a Tablet PC–by visiting http://www.TabletPCPost.com/Search. You do need a browser that is capable of running Silverlight, however.

I think I down-sampled the video too much so it’s kind of hard to see what’s going on. Fortunately, I wrote large most of the time. I’ll see if I can fix the video.

Update: Want to learn more about InkWell? Check out this blog post on SkinYourScreen.com about InkWell. It does a pretty good job of walking through InkWell’s capabilities.

Loren
Lorenhttp://www.lorenheiny.com
Loren Heiny (1961 - 2010) was a software developer and author of several computer language textbooks. He graduated from Arizona State University in computer science. His first love was robotics.

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