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Tuesday, May 13, 2008 | |
In this talk, I will present a brief overview of ThinkScribe and discuss some of the challenges faced by Pen computing in the past and how ThinkScribe addresses some of them. I will then move on to talk about the handwriting recognition engine that forms a key component of this device. The recognition engine uses hidden Markov models to model individual characters. A combination of the character models and smart search strategies result in a real time large vocabulary handwriting recognition system. Although the system offers a user the convenience of operation `out of the box', i.e. without any training on the part of the user, there is a significant improvement in accuracy when trained for an individual's handwriting. In this talk I will briefly talk about strategies that are used to adapt the writer-independent models to a user's writing style.
The talk will conclude with a list of open research areas in large vocabulary unconstrained online handwriting recognition and future directions of on-line pen computing.
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